A case for attribution
theory in public
accountability
A.M. Polak
01-07-2015
Table of content
Accountability: a tale of responsibility and attribution? ......................................................................... 2
Public accountability is holding someone responsible ........................................................................ 2
The status quo: Interest based attribution of responsibility ................................................................. 9
Attribution according to social psychology ....................................................................................... 13
Understanding agent behavior: attributional theory .......................................................................... 14
Understanding forum behavior: attribution theory ............................................................................ 17
Further: additional uses and methods to test applicability ................................................................ 24
Conclusion ......................................................................................................................................... 26
Attributing cause in oversight: the role of consensus, distinctiveness, consistency information .......... 38
1. Introduction: accountability and attribution .................................................................................. 38
2. Theoretical framework .................................................................................................................. 42
2.1 Attribution theory .................................................................................................................... 42
2.2 Proving grounds and the three stages model in practice: oversight by inspections and
regulatory authorities. .................................................................................................................... 47
3. Method: proposed materials and analysis...................................................................................... 53
4. Data ............................................................................................................................................... 57
4.1 Descriptives ............................................................................................................................. 57
4.2 Regression ............................................................................................................................... 59
4.3 Additional tests ........................................................................................................................ 65
5. Findings, limitations, and discussion............................................................................................. 66
5.1 Findings ................................................................................................................................... 66
5.2 Limitations............................................................................................................................... 67
5.3 Conclusion ............................................................................................................................... 69
Bibliography .......................................................................................................................................... 71
Appendix A: Materials .......................................................................................................................... 75
1
Accountability: a tale of responsibility and attribution?
There are many typologies in the field of public administration of accountability to describe
the relation between forums and agents. However, these typologies pay little attention to why
a forum holds an agent responsible for certain matters. Here we will propose existing social
psychology theory as a as a central mechanism in accountability. This article will elaborate
on these theories and on how they could tie in with existing public administration concepts.
Finally, a research agenda is proposed.
Public accountability is holding someone responsible
Public accountability is the name of a group of conceptual relations that make government
‘work’; It describes the operation of institutional relations between organizations, groups and
individuals involved in and with government. This concept presumes that, on the one hand,
there are parties that have to give account of their actions and decisions. On the other hand,
there are parties that receive these accounts (Pollitt, 2003: 89). These former parties, typified
as principals or forums, can exercise a degree of control over the latter parties, agents or
actors, on the basis of these accounts. The adjective public refers to the context, the object
and standards in accounting perspective; the accounts are public, regarding a public setting,
and regarding manners that are of concern and interest to the public (Bovens, Goodin,
Schillemans, 2014: 7). The account receiving party is involved as it is interested or influenced
by the first party. This other party either has the role of a stakeholder or a principal. This
principal-agent template of public accountability takes many forms in government. In this
article we are interested in how findings by both the forum and agent come about within these
various relations.
Within all these public settings there are four types of accountability mechanisms at play
(Romzek & Dubnick, 1987). Each of these has its own rules, logic, and dynamics that shape
the principal-agent relationship. These types describe the roles of the actors, in which context
2
these are set and what mechanism binds the actors. However, these accountability
mechanisms do not explicitly explain what causes the actors to behave in the manner that they
do.
For example, the behavioral link is missing in the political accountability mechanism. This
mechanism is the most fundamental to democracies. The agent here is a representative of a
loosely coupled group of constituents (Romzek & Dubnick, 1987). These representatives take
the form of politicians. The mechanisms at play revolve around gaining votes by gaining
favor with the constituents. The perception of favor translates into votes, via which candidates
are selected and are able to maintain or lose their position. This mechanism of accountability
by representation is also at play with the selection of representation within special interest
groups, although appointment is not necessarily arranged via formal elections. The
mechanism of favor is mentioned, but the mechanism does not describe how this mechanism
works. It does not mention how the forum decides who to favor and who to blame. The same
pattern of glossing over this fundamental question can be seen with the other three types of
accountability, which are more predominant in the domain of civil service.1
The most prominent example of legal accountability, or vertical accountability, is the default
within public administration: accountability towards ministerial departments. Clear norms are
developed in the Netherlands for executive organizations that report to the ministries (van
Montfort, 2009). This is an inter-organizational mechanism as both organizations are bound
by legal sanctions and enforced by formal contracts and rules. The reported topics are quite
broad and contain both information about the services supplied and performance, but also the
1
It should be noted that in practice all four forms of accountability are to some degree at play in an organization
in a typical public setting. This is due to the fact that many public organizations are involved two or more of
these settings, and thus have multiple types of principals. (see e.g. Romzek & Dubnick, 1987; Romzek, 2000;
Koppell, 2005; Schillemans & Bovens, 2011).
3
collection and spending of public money, and operations. Most commonly used accountability
documents are quarter or annual reports. Additional accountability is oral, both organized and
unorganized. Although, information requested by departments are not always just for
accountability purposes – this also might be for evaluative or trend purposes – it is often
perceived as such by the accountee. The request for substantial amounts of information by the
departments is due to the pressure to minimize risks. Additionally, information might reach
ministries via the media. The formal informational demands for the reporting organization
depend on the scope of responsibility of the minister. This varies for the minister from system
variant, and thus the broadest scope, to more specific delineated responsibilities. Again, the
mechanism describes a setting and actors involved, but why the actors exact the competencies
that they have over others remains unclear; How is the information received by the forum (the
ministry) linked to its actions?
This is also visible in the intra-organizational mechanism of bureaucratic accountability. This
mechanism consists of supervision, rules and regulations within an organization. Many public
organizations have a two-tier-model for internal supervision. This means that they have
instated a separate supervisory board within the organization (Boers & Monfort, 2009). These
boards have three main tasks: First, they supervise the executive board. This is done by the
means of approving the annual report, budgets, changes in regulations and appointing the
accountant. Second, the board gives advice to the executive board. Third, the board appoints,
rewards and judges the performance of the executives. Additionally, all organizations
comprise of forms of bureaucratic accountability in the form of individual accountability. This
is any form of accountability given by the individual to supervisors. This can be either
arranged in formal manners, in accordance to rules and regulations, or informal. An example
of an environment with more professional accountability is that of inspections and regulators.
The classical inspection is a department and is directly under ministerial responsibility
4
(Yesilkagit, 2009). It operates on specific legally appointed tasks. Most inspections focus on
public sector, but some also on private sector. There are three main tasks for these
inspections: initiation of inspections, inspecting, and formulation of opinions and sanctioning.
Most organizations that fall under the inspection are granted relative autonomy and discretion
in the execution of their job, but have to meet performance expectations as intended for their
clients and customers. Similar to the mechanism of legal accountability, with bureaucratic
accountability and professional accountability we have typologies of the settings, the actors
have certain roles, with one actor having a set of instruments to exact some power over others.
But, why the instruments are used and based on what information, in such a way makes these
mechanisms work, is only implied, but never elaborated.
So, although expansive, accountability literature has not really explicitly focused on the
mechanics involved in holding actors accountable in these accountability mechanisms. From
various other typologies we know how, for example, different types of forums have an effect
on accountability (Schillemans, 2012). We know that multiplicity of stakeholders has an
impact on a mechanism (Romzek & Dubnick, 1987; Romzek, 2000; Koppell, 2005;
Schillemans & Bovens, 2011). All these typologies, however, do not explain how a parties
form an opinion about whether or not another party is responsible for an action or outcome. In
fact, by not treating this issue explicitly we cannot say anything about the fundamental debate
on the need of supervision. We do not know how input leads to actions and outcomes in
accountability. This is worrisome, because due to this we simply do not know why the
mechanisms that make government ‘work’ , actually do work.
Despite this missing link present, most of these mechanisms do contain the same core
elements of the accountability model: The interaction between the two parties is universally
describable in three stages (Bovens, 2007). In the first stage agents inform a forum about their
actions and decisions. This happens on a voluntary basis via various manners. It forms a part
5
of the agent’s normal routine. The second stage revolves around questions posed by the forum
and the agent’s follow up response. The forum poses questions based on both information
given by the agent, and additional external information. When the given information does not
suffice, the forum will demand further answers from the agent. The final stage is set when
judgment is passed by the forum and the agent is faced with the consequences. The forum will
try to exercise what power it has over the agent to correct its wrongdoings. These three stages
form the stages of accountability. However, as stated, little is told about how members of a
forum come to a judgment about the agent. Applied to the three stages model, we would
assume that the forum receives information in the first two stages, and applies this
information in their judgment in the third stage. So, to be more specific, the question of
interest is: If negative events occur in the first two stages, what type of information causes the
forum to attribute responsibility to an agent in the third?
To answer this question we first have to elaborate the concept responsibility. This is a rather
ambiguous concept, but is prevalent in public administration literature: For example, Stone
(2002) gives us four typologies of cause used in policy formulation. One of the specific uses
that cause has in policy formulation is assigning blame and responsibility. Actions in this
typology can be perceived as unguided or purposeful and consequences can be either intended
or unintended. They could be seen as agents working on the factors that determine attribution
for the forum. The same is seen after a crisis; actors engaged in blame games make strategic
choices along three dimensions: severity, agency and responsibility (Boin et al., 2005). All
these various theories lean on a party assigning responsibility to another.
Broadly discerned, responsibility has five interpretations (Hart, 1968:211-230 in Bovens,
1998). First, the meaning of responsibility could equal the sense of someone or something
being the cause for a certain effect. This means that to be responsible for something is to have
6
caused it or to have done something with said outcome as a consequence. Not just people’s
behavior can be seen as causes, but also more abstract matters such as institutions and
circumstances can be held responsible. Second, being responsible can be noted as being
accountable. This refers to being responsible in a political, moral or legal sense. Third notion
of responsibility is the mental capacity of an individual. Responsibility here is synonymous
with compos mentis (soundness of mind) as opposed to insanity. Forth notion is the notion of
responsibility as a given task or duty. This equates, for example, to holding an office or
function within an organizations. From it follows certain duties and having certain
competencies. Responsibility here refers to the appropriateness of decisions and actions made
in this capacity and is synonymous with authority. Last, responsibility can be discerned as a
virtue. A person could for example be described as having a sense of responsibility. This
person would take his or her tasks and duties seriously, only acts after due deliberation, and is
considered answerable for his or her actions. Many of these notions are not mutually
exclusive, but rather overlapping.
More interesting is the distinction between notions of active and passive responsibility
(Bovens, 1998). Under active responsibility fall notions of responsibility that are tied to a
perception of norms on which actions and decisions might have an impact. It is tied to a
consideration of the consequences of actions and decisions. It also contains questions about
what discretion is granted with given autonomy and how taken actions affects autonomy of
others, taking obligations seriously, and having a conduct that is conform to applicable codes.
This is in short, acting responsible and taking responsibility. This active category of
responsibility notions lies predominantly with the agent side of the accountability framework
as the actor is considering his or her own actions and decisions. The passive category consists
of notions that involve observing transgressions of norms, finding causal connection and
7
blameworthiness with others. These are part of passive responsibility. This category of
responsibility belongs to the forum side; they pressure this passive responsibility on the agent.
Both passive and active responsibility are highly relevant to our main question: Responsibility
as the degree in which an actor is perceived to be the cause of a negative event. To what
extent is the perception of cause linked to the assigned tasks, the particular circumstances, or
the actor itself? How do people come to conclusions about this? Answering this questions is
how information from the first two stages of Bovens’ (2007) accountability model leads to the
outcome in the third stage. The perception of degree of responsibility based upon information
from the first two stages and acting upon it in the third is what forms the link between these
stages. This question of responsibility in the notion of cause. Only by establishing causality is
it possible to assess blameworthiness and the violation of norms an actor. However, before
delving into the mechanisms that lead to establishing causality, and thus responsibility, we
must look at to whom it can be attributed.
Agency of responsibility can be put on various organizational levels. First, responsibility can
be put on the corporate level. In this the organization is presented as if it were a single entity.
In this manner the origination is held accountable for the collective outcome (Bovens, 1998:
53-54). Hierarchical accountability is another solution. Here the responsibility of the
organization lies at the top of the organization. Examples of this practice are a minister,
director or chief executive officer or commander in chief who is held responsible for the
organizations performance and actions. The reasoning behind this lies with the fact they are
in position to decide and steer organizational policy, both intended and implemented (Bovens,
1998: 74-75). Lower hierarchical ranks within these organizations often do not carry external
responsibility; concerns are to be addressed internally by the leaders. Another possibility is to
put responsibility at the level of the collective, in which all parts of the organization bare the
same responsibility. This might prove a necessity in certain circumstances in which it is
8
difficult to trace responsibility to the individual level. In this manner all individual member of
the collective are responsible for the conduct of the whole. The opposite of placing
responsibility on a collective level is to lay it with the individual. Each member of the
organization is held liable according to the extent to which and in so far as he or she was
personally contributed to the offending conduct on the part of the complex organization.
These are the four ideal types of scales of responsibility of and within an organization. These
are the four possible levels to whom cause can be attributed on the agent side in the public
accountability model.
The status quo: Interest based attribution of responsibility
Thus, there are various levels where responsibility can be attributed to within an organization,
each with inherent considerations involved. But, this does not explain why people attribute
blame. The most commonly used assumption in accountability literature to explain the
attribution of responsibility fall under the principal-agent view (Schillemans, 2013). This is a
rational choice based strand of theory (Peters, 2012). Blame and responsibility here seem to
be “obviously” explained by the actors’ self-interest or social constructivism (the role the
party has).
Literature on blame and responsibility in public administration is mostly confined to the
context of crises. This makes sense to a certain degree, given that these are the most salient
circumstances of public sector failings. However, these are extra-ordinary circumstances and
given the impact of these events they are mostly played out within the political accountability
mechanism.
There are some known factors that influence the perception of responsibility that could be tied
to the mechanism of political accountability. If we equate blameworthiness of a minister to
being forced to step down, we see that certain factors influence the occurrences of this. In the
Netherlands we see that ministers who have some experience as Member of Parliament are
9
less likely to be forced to step down (Bovens, Brandsma & Thesingh, 2014). Same goes for
ministers who survive two votes of no-confidence; after that they survived any following vote
as well. This points towards the minister being able to play the blame game. Ministers who
are from a party that is not needed for a parliamentary majority are as well more likely to be
forced to resign. This indicates that self-interest of co-governing parties might play a role in
their resignation. The same might apply for the higher resignation rate of ministers from a
new party. This as well points to a self-interest driven reasons for a coalition partner to get rid
of the ministers in question. Their lack of networks within parliament, and experience in
organization and politics might be a liability. In the case of British ministers we see entirely
different dynamics at play for blameworthiness. This is mostly due to the institutional
differences between the two countries. Given that the United Kingdom has a majoritarian
system, the prime minister has more liberties to reshuffle and re-staff his ministers, and thus,
British ministers are forced out of office more often (Bovens et al., 2014). Again, this more
frequent usage of forcing ministers out of office due to having more institutional room to do
so, is something that can be seen as the result of rational-choice.
In further public administration literature the assignment of responsibility is mostly portrayed
as the result of actors framing situations to their advantage. When a crisis occurs,
organizations and individuals try to exploit this maneuver in their favor and minimize the
perception that they are to blame. They try to promote their own proposals, further their
popularity and harm enemies (Boin, 't Hart and McConnel, 2009). Actors redefine issues by
proposing the most convincing frame in the hope of it gaining dominance over others. Actors
engaged in blame games make choices along three dimensions to achieve this: Actors try to
reframe severity of the issue, actors try to shift agency of the cause, and actors try to re-assign
responsibilities (Brändström and Kuipers, 2003; Boin et al., 2005; Bovens et al., 1999). The
perception of legitimacy of these choices depends on timing, on the setting in which they are
10
used, credibility of the actor and the manner of presentation. Therefore, outcomes in terms of
responsibility are predominantly understood as the result framing contests (Alink et al. 2001).
Thus, the current view implies that the forum’s judgments are formed in an unstructured
manner, determined by games played by the agents and the result of a narrative gaining
dominance (’t Hart, 1993; Brändström and Kuipers, 2003; De Vries, 2004). This self-interest
based explanation for the assignment of responsibility seems fitting as it is compatible with
the dominant self-interest based theoretical assumptions within accountability, if present.
This leaves us currently with predominantly self-interest driven explanations. This dominant
view of self-interest as sole explanation for the workings of public accountability has some
problematic limitations.
First, this attribution of blame based on self-interest is more fitting in a political accountability
system, but it tells us little about the contexts in which an actor has no reason to play blame
games. The amount of studies of responsibility and blame involving legal, expertise and
bureaucratic accountability mechanisms seems limited. We cannot contend that in every
public accountability setting the assignment of responsibility is equally highly politicized.
Certain organizations’ behaviors are characterized as less self-interest driven than others; not
all judgments are seen as the result of self-interest. Instead, judgments can be based on
technical or legal considerations when typified as operating within these systems.
Additionally, there are situations where the forum logically cannot be conceived as being
involved in blame games. A forum in the standard accountability model is assumed not to
have an executive role as its agents do. In these situations the forum is standing, as it were, so
far above the playing field that it cannot reasonably be held responsible for the outcomes
produced at the level of the agents. Therefore, in these situations the forum should, again,
have no interest or incentive to engage in blame games when assigning responsibility.
Another problem occurs with interest based attribution if we were to say that attribution by
11
the forum is based on influence of the forum’s forum (e.g. media, stakeholders or political
actors) In this case we are only placing the problem of self-interest based attribution on
another plateau. If an actor is truly interested in finding the root cause of an outcome, then
attribution based on self-interest alone makes little sense.
Second, this sole self-interest based view is contradicted by findings. Research has shown
actors behaving in manners that are not compliant with the principal-agent theory (see
Brandsma and Schillemans, 2013; Breaux et al., 2002; Benjamin, 2008; Kassel, 2008;
Dubnick & Frederickson, 2010; Skelcher, 2010; Olsen, 2013).Third, and most worrisome,
blame games are not compatible with the promises of accountability. Normatively, for the
accountability to work according to literature, it requires judgment to be appropriate to the
performance of the agent. Public accountability holds the promises of democratically
responsive government, improvements in efficiency and effectiveness of performance of
government agencies, ethical public sector workforce and enhanced capacity of government
to generate just and equitable policy outcomes (Dubnick and Frederickson, 2011 in Dubnick,
2014). If the mechanism of accountability is an arena of self-interest based narratives, then it
becomes inconceivable that this mechanism can realize these promises. When the forum
punishes or rewards actors arbitrarily as an inevitable result of this mechanism, then these
promises are not obtainable. Blame-shifting and blame avoidance limit the capacity of
accountability to control agents in their actions and performance (Hood, 2002). The learning
and corrective capabilities of the system become limited. For achieving the positive working,
the consequences in the form of judgments must be appropriate to the agent’s performance.
This requires an adequate attribution of cause by the forum; attribution under this condition
cannot solely be the result of blame games. In crises, quality of accountability depends on the
actors showing restraint and proportionality. Correctly assigning causal credit or blame is
assumed to increase the frequency of success and reduce the frequency of failure (March and
12
Olsen, 1995 in Olsen, 2014). This is unobtainable under blame games. Even less if
responsibility is pre-established, when the forum itself is partaking in these games.
Accountability becomes hollow when investigation and debate becomes merely a ritual (Boin
et al., 2005). We certainly cannot maintain that this is always the case in practice and have to
find a better understanding of attribution of cause if we wish to understand the working of
accountability.
Attribution according to social psychology
The starting point for alternatives for understanding judgment is to look at the attribution of
responsibility in social psychology. The appliance of social psychology in understanding
accountability is not uncommon. The social contingency assumptions are an existing
alternative to rational choice in accountability. This alternative theoretical view sees
accountability as a bridging element between the individual and social environment (Lupson,
2007; Mansbridge, 2014). The behavior of individuals is assumed to be influenced by intrapersonal cognitive processes (Koch & Wüstemann, 2014); such as studied in social
psychology.
The cognitive process which seems most relevant here is that of attributing responsibility in
terms attributing cause. This, as responsibility is seen as the "psychological adhesive" that
connects actors with events (Schlenker et al., 1994). The main concepts from social
psychology regarding this are the concepts of attribution and attributional theory. These were
first formulated by Fritz Heider (1944 in Fösterling, 2001) and derived from the classic works
of John Stuart Mill (1872/1973). It describes the attribution of causality given so-called
covariation of factors, i.e. the difference in observation in presence and absence of certain
things that coincide with the occurrence of an event. This field has mainly diverged into two
separate streams, attribution theory and attributional theory. In the following paragraphs I will
explain the difference between attributional and attribution theory and elaborate how
13
attributional theory can be applied to Bovens’ (1997) active responsibility and more
interesting, attribution theory to passive responsibility.
Understanding agent behavior: attributional theory
Attributional theory deals with how people attribute cause, including themselves as a potential
cause (Weiner, in Fösterling, 2001). The theory is based on the work of Kelley (1967 in
Fösterling, 2001) and Heider (1958 in Fösterling, 2001) and is related to social learning. This
theory assumes that the perception of success or failure is based on a why question. This is
primarily tied to the question of locus of control. The locus of control refers to whether the
actor could have done something about the outcome (internal locus) or it was due to
circumstances (external). The second dimension is stability of this locus of control, being
either stable or variable. This leads to a quadrant of attributable causes, being ability (internal,
stable), effort (internal, variable), task difficulty (external, stable) or mere luck (external,
variable). Meyer (1973 in Fösterling, 2001) was first to demonstrate this empirically: Subjects
indicated a stronger decrease in success expectancies when failure was attributed to stable
causes (their ability and task difficulty) than those who tended to attribute failure to variable
causes (chance and effort). Similar results have been found quite often (See: Fontaine, 1974;
McMahan, 1973; Weiner, Nierenberg & Goldstein, 1976). The dimension of intentionality
was added by Rosenbaum (1972 in Fösterling, 2001). This was found to be an important
determinant for experiencing resentment or empathy given the perception of the locus of
control. Weiner, Russell and Lerman (1978) found that the expression of guilt is connected to
attribution as well. They argue that this is due to an internal and controllable self-attribution.
Blame and praise are tied to the perception of effort. This points to internal causes (Weiner &
Kukla, 1970). Furthermore, it is shown that an expectation of high ability is most desirable as
it leads to expectations of success. (Covington & Omelich, 1979; Jagacinski & Nicholls,
1990). This is however, found to be a double edged sword. People tend to equate high effort
14
to relative low ability and attribute failure to low ability in spite of effort (Brown & Weiner,
1984).
Plenty of studies have been made into attribution in organizational settings next to these
general findings (see the full review of Martinko, Douglas & Harvey, 2006). Here we will
summarize the most important relevant findings. The first category is studies related to
performance attribution of subordinates. The first work regarding this was done by Lord and
Smith (1983). They suggested that attributions can be used to refer to personal qualities such
as leadership and responsibilities for an event. Various factors have been found to impact
negative attribution performance. Wood and Mitchell (1981) demonstrated that external
accounts for poor performance reduced the amount of responsibility assigned by supervisors,
and that both external accounts and apologies reduced the amount of punishment by
supervisors. The same relationships have been described by Weiner, Figueroa-Munoz, and
Kakihara (1991) and Gundlach et al. (2003). They found that excuses and apologies can shift
locus of causality, but also the perception of stability and controllability of the situation.
Attribution of performance has also been studied in relation to teams. A main finding is that
team performance and individual performance are often attributed to different causes. This is
also known as the team halo effect. It refers to the tendency of evaluators to hold individuals
within teams responsible for negative outcomes while attributing positive outcomes to the
team (Naquin & Tynan, 2003). This tendency is also found in larger groups, such as
departments. Some individuals are more likely to be singled out as responsible for negative
outcomes. These are for example individuals who deviate from collective norms and thus
perceived with low consensus. This was even found for demographic characteristics. Also
deviating behavior is more likely to be blamed for poor performance (Ramsay et al., 1997).
The factors of attribution have been found to be applicable to teams and poorly performing
members (LePine and Van Dyne, 2001; Jackson and LePine, 2003). Found was that when
15
group members attributed poor performance of a group member to low task-related ability,
then this was seen as uncontrollable. This resulted in sympathy for the low-performer,
working around him, providing him with more training and the group was less likely to reject
him. If low performance was attributed to the lack of effort, then it was seen as highly
controllable. As expected, sympathy was lower, a higher chance of rejection was reported and
the team was less likely to work around him or provide training. Silvester et al. (1999)
performed an attributional analysis of key stakeholder groups in a multinational corporation
who were involved in a culture change program. They found evidence indicating considerable
intergroup differences in how managers, trainers, and trainees perceived the change process.
Hence, the results suggest that attributions can operate at a group level when group members
share an underlying causal schema for interpreting important work-related events. Fortunately
for accountability in institutional arrangements, some research has been done regarding interorganization and attribution. Group membership (in-group vs. out-group) biases attributions
about controllability. This in turn has influence on feelings of gratitude or anger and the levels
of cooperation and competition at both intra- and inter-organizational levels (LePine and van
Dyne, 2001; Jackson and LePine, 2003).
A second relevant attribution field is the attribution of ethics, moral, and justice as founded by
Jones and Nisbett (1971 in Fiske & Taylor, 2007). Payne and Giacalone (1990) argued on the
basis of their work that the same action can be seen more or less moral depending on whether
you are observer or actor. Weiner (1995 in Martinko, 2006) pointed towards a more complex
relationship. For responsibility we must believe that an act was caused by the actor’s internal
characteristics; that he or she had control over the action and that it was intended to happen.
Observers are more likely to see another party as responsible for wrongdoing when they
attribute wrongdoing on controllable and stable causes. Also in criminology we see this:
Grasmick and McGill (1994) and Cullen, et al. (1985) see a difference between dispositional
16
attributions and situational attributions. The attributions cause an accordingly more or less
severe judgment. Lastly, Martinko et al. (2004) describe how information and attributions
lead to various types of perceptions of justice.
These studies are quite relevant for explaining agent behavior and thus active responsibility. It
shows how in various manners the actor places causality of outcomes and various
consequences thereof. This, when applied to an agent in the public administration sense, could
prove useful in understanding actor behavior in the three stages model of accountability as an
alternative to pure self-interest as a motivator. However, if we were to understand the core of
the accountability stages model we have to look at concepts that apply to passive
accountability. Coming from the framework of accountability, we are interested in the
attribution of cause from the perspective of an observant, rather than a participant. The forum
has no executive role in the three stages model; in line with the common assumptions of
accountability frameworks responsibilities – in the sense of duty, role or task – of executive
and principal are demarcated and separated. Since the actor itself is considered a potential
cause in attributional theory the second theory strain of attribution is more applicable in
understanding the workings of the public accountability model.
Understanding forum behavior: attribution theory
However, if we wish to understand the actions of a forum (passive responsibility), then social
psychology offers us causal attribution theory. Attribution theory prescribes that cause is
prescribed to the actor, the target or subject of the actor’s actions or particular circumstances
on the basis of absence or presences of factors in information. This attribution theory was first
conceptualized by Kelley (1967 in Fösterling, 2001). Kelley’s model proposes factors of
consensus, consistency and distinctiveness in agent behavior as determinants for attributional
outcomes. These factors are information regarding behavior of an actor or agent. Consensus is
established if an individual is perceived to behave similar to his or her peers. Consistency
17
consists of the perception of similar behavior or characteristics over various similar instances
in time. Distinctiveness is established if the same behavior or characteristics are displayed in
multiple dissimilar instances such as various tasks or interactions. The attribution is
consequently made to a person or object (the actor), an entity or subject (the target or subject
of the agents action), or the particular occurrence or circumstance. A personal or actor
attribution comes about when low consensus, low distinctiveness and high consistency are
perceived by an individual. A target, or stimulus, attribution is made when a high consensus,
high distinctiveness and high consistency is perceived. Finally, an occurrence, circumstance
or time, attribution is made when there is low consensus, high distinctiveness and low
consistency (Kelley, 1973 in Fösterling, 2001). Since its first empirical test the theory has
been applied to attribute various cases, such as emotions, opinions and actions. Given our
interest in terms of accountability we will limit ourselves to the use in accomplishments,
especially those that lead to a negative outcome. An example of a negative accomplishment
statement is for example: “George translates the sentence incorrectly” (taken from McArthur,
1972).
To apply this on a public setting example, based on the theory, we could formulate the
following information: “The project leader handed the results in late. Other project leaders
were on time. The project leader hands in other work late as well and has been late before
with the same results.” According to causal attribution theory this configuration should lead to
a higher attribution of cause (blame/responsibility) to the person, i.e. the project leader. If we
were to configure the information as: “The project leader handed the results in late. Other
project leaders were late. The project leader hands in other work on time and has been late
with the same results before.” In this case we would attribute cause to the target (the particular
results). So, as proposed by this theory, the attribution of cause, and thus responsibility,
follows from a relative context independent informational configuration. Here is the last
18
configuration to make this exercise complete: “The project leader handed the results in late.
Other project leaders were on time. The project leader hands in other work on time and never
has handed these results late.” In this case, people are likely to attribute the cause of being late
to this particular occurrence. For this paper we are interested in applying these findings in a
real world public accountability setting and argue that it forms part of accountability
processes on a micro-level, fitting the three stage accountability model.
The causal attribution theories have subsequently formed a large body in the field of social
psychology. After the initial empirical work by McArthur around 30 papers have been
identified as supporting the covariant model in some manner. These are mostly variations on
the original experiment. McArthur, L.Z. (1976) demonstrated that consensus information was
of lesser influence than distinctiveness. Major (1980) presented subjects with limited
information and allowed them to query for additional information regarding consensus,
distinctiveness, and consistency. Subjects showed a preference for consistency information,
above distinctiveness or consensus. Hilton and Jaspars (1987) explicitly compared negative
and positive target events and found that the attributions are the same.
There are some remarks regarding Kelley’s initial attribution model. Malle (1999) noted that
attribution should take account of a separate dimension of intention with the actor, as this lead
to a different attribution. This finding is in line with the notion that responsibility can be
defined as both as a cause and a conscious act of an actor. Later work in attribution refined the
Covariation model, such as those from Cheng and Novick (1990), Försterling (1989),
Hewstone and Jaspars, (1987). Hilton and Slugoski, (1986), and Pruit and Insko (1980). Most
of these studies support Kelley’s model in main lines, but propose additional information
requirements or a method of analysis that differs from the simple covariation of the factors in
Kelley’s model, such as information regarding intention.
19
This theory is promising in various manners. There is a certain similarity in the working of
concepts. In policy, for example, it is partially found to be based on perception of intent of
actors. Perceiving actions as unguided or purposeful, and consequences as either intended or
unintended, leads to different policy decisions (Stone, 2002). The same is seen after a crisis;
actors engaged in blame games make strategic choices along three dimensions: severity,
agency and responsibility (Boin et al., 2005). It also might explain differences in process and
outcome accountability. If the agent only reports the outcome of its actions the forum lacks
information about the agent such as consensus, distinctiveness, and consistency or even
internality or externality from the attributional theory. In general, the theory might explain
why certain forum judgments are made in cases. There are some other factors that make it
rather applicable to the public setting: It is suggested that Kelley’s model of attribution is
applicable in settings where causal information is either missing or ambiguous. People prefer
contextual causal information over information regarding consensus, distinctiveness, and
consistency, when asked to formulate an account (Ahn, Kalish, Medin & Gelman, 1995). This
is what makes this theory particularly interesting, judgment patterns that are made in cases
‘objective and factual’ information is missing. It offers an explanation for attribution in
ambiguous and in complete information, rather than just based on self-interest. It offers us
new insights in the micro-setting of accountability of which the commonly studied aggregate
of accountability is comprised. The micro-setting is in this context defined as the judgment of
an individual within a forum. Studies currently do not incorporate this individual level. The
micro-setting offers a look at ‘clean’ attributions as the influence of a third party is limited;
these attributions take place before any possible blame gaming. It offers the mechanisms
linking the stages accountability, rather than the current (inexplicit) assumptions.
Neutral attribution in this case can be noted as not purpose guided. This does, however, not
mean that it is objectively neutral; the existence of biases has been demonstrated quite
20
frequently for this type of attribution. A famous experiment showed that people bias an actor
rather than situational circumstances (Jones & Harris, 1967). People attributed pro Castro
stance essays to be the result of an opinion that the author held, even when these people knew
that the author was given the assignment to write a pro Castro essay. This tendency is called
the correspondence bias or fundamental attribution error (see Gilbert & Malone, 1995 for
review). Another point is the underuse of consensus information. Consensus explains
significantly less variance of the attributions, compared to distinctiveness and consistency
(Nisbett & Borgida, 1975). However, when participants were asked what information they
would like to have before making an attribution, it is consensus that was most often asked for
(Hilton et al., 1988). On a related note: individuals have a bias towards their own attitudes and
behaviors. They believe that theirs are met with high consensus. For example, Ross et al.
(1977) asked college students whether they were willing to carry certain posters. The people
who agreed estimated that 63.5% would do this as well. People who refused to carry the
poster estimated that only 23.3% would comply and carry the poster. It is theorized that this
effect stems from socialization. The observations most available to the participant lead them
to find the same behavior in most of their peers. These are inferences about whole population
based on the sample consisting of their peers. With these peers they are more likely to share
certain similar characteristics, views and behaviors. A summary of this effect can be found in
Marks & Miller (1987). Another bias is the self- serving bias for success and failure. Success
is disproportionally reported as caused by internal causes (the person themselves) and failures
more so external (situational) (Miller & Ross, 1975; Zuckerman, 1979). This is found to be
both valid for persuasion (interpersonal) as for skill related tasks. The motivational factors
assume that emotional states, needs and desires, such as positive self view, are responsible for
the actor-observer effect (Pyszczynski & Greenberg, 1987). This is a self worth protecting
mechanism. Another motivational explanation which is relevant is the notion of Miller,
21
Norman and Wright (1978). They found that the willingness to control and predict a person’s
actions leads to an intensification of the tendency to attribute the behavior to dispositional
factors (i.e. internal, to the person’s ability or behavior).
Next to the obvious self-serving motivation, it has been theorized that this tendency arises
from cognition. Miller and Ross (1975) have suggested that this is due to people more often
observing their own covartion in actions and success, than with actions and failure. Meaning
that if a failure occurs it can happen despite the shown effort. For success, however, some
degree of action has to be taken, no matter how objectively insignificant. Secondly,
individuals only engage in activities if they perceive a good chance of succeeding. People
mostly start with things which they before starting perceive themselves being able to do.
Failure in this assumption only takes place not because we don’t have the ability (internal),
but because some external factor (Stephan & Gollwitzer, 1981; Miller, 1976).
Beckman (1970) suggest that the self-serving bias is related to the fact that observers do not
‘see’ actions undertaken by others, whereas the others are more aware of these facts. This is
related to the actor-observer asymmetries in attribution. People tend to attribute their actions
to situational requirements, whereas the observers tend to attribute the same actions to stable
personal dispositions (see also Watson, 1982 for review; Stroms, 1973, Nisbett, caputo, legant
& Mareck 1973). Again, there are two possible mechanisms at play: informational and
motivational. The informational mechanism simply assumes that the actor has more
information regarding the situation compared to an observer. This information for the
observer is in terms of the Kelley cube mostly based on consensus. Consistency and
distinctiveness are mostly less available and thus lead to an unrealistic person attribution. This
seems supported by findings that show dispositional attributions decreased when
acquaintanceship was increased with the person about whom they had to judge (Golberg,
1981; Nisbett et al., 1973).
22
Next to the informational and motivational stances in the origin of biases there is the
difference in perceptual perspectives in actors and observers. This is due to the fact that actors
focus on situational demands. Observers only observer the actor, yet there is a difference in
what is salient to both parties. Sometimes even visual differences are enough to make a
difference (Storms, 1973). Another bias is intergroup based regarding characteristics such as
gender, ethnicity or religious persuasion (Taylor & Jaggi, 1974, Deaux & Emswiller, 1974).
In general, socially desirable behavior is attributed more often to internal causes for the ingroup, while undesirable behavior was attributed less often internally. This effect, however,
has not been demonstrated not to be universally consistent (Hewstone, 1990; Hewstone &
Ward, 1985). Another offshoot is the conversational processes involved in attribution (Hilton,
1999). Attribution often takes place in social contexts such as converstations; linguistic rules
appear to be a determinant of the attributions that individuals communicate (Fösterling, 2001).
The verb-causality effect, as it is called, show that minimal information in the form of ‘a does
b’ is often perceived to be enough to draw some causal information upon (Brown & Fish,
1983; Garvey, Caramazza & Yates, 1976). This bias towards the object of the sentence has
been affirmed quite often (Garvey and Caramazza, 1974; McArthur, 1972). This is because
subject and the object of the sentence constitute a basic schematic meaning which leads to
different causal attributions (Brown & Fish, 1983; Semin and Fiedler, 1988, 1991; Rudloph
& Försterling, 1997). This leads to another covariotion based explanation. Basically, a
twofold explanation is given by the difference in degrees of implied control and universality.
First, emotional sates are experienced by most humans; almost all people imagine how they
would respond in a certain situation. These can be seen as notions of consensus and
distinctiveness to compare the given information with. However, with action verbs a
voluntary control is implied. Some sentences might indicate low consensus, as in people can
choose to act one way or another, but it is tied to the same response by the person in various
23
other situations (distinctiveness). If the comparison leads to a finding of low distinctiveness
and low consensus then this leads to an actor attribution.
Further: additional uses and methods to test applicability
Thus, attribution theory offers some insight that might be valuable in understanding the agent
and forum and can build upon the distinction between active and passive responsibility. As
noted, especially Kelley’s attribution theory is interesting as an explanation of the behavior of
forums. This forms the unaddressed fundaments of the central three stages model of
accountability. The application of these theories to the field of public accountability is,
however, just one aspect. Relevance for other fields of public administration is imaginable as
well. The theory of casual attribution potentially explains something about the process of allimportant agenda setting. On the one hand, this is useful as policy often is designed based on
the assignment of responsibility (Stone, 2002). On the other, these theories help understanding
why, out of all conceivable issues, attention is paid to the ones that do end up on the policy
agenda (Kingdon, 2002).
Thus far in this article we have elaborated the most important and relevant insights in
attribution from social psychology that might be applicable to public accountability. These
theses are, however, untested and unproven in public administration contexts. The manner in
which social psychology hypotheses are tested might not make them directly applicable to our
specific field. Social psychology has a tendency to try to find ‘universal laws’ regarding social
cognitive processes. Public administration on the other hand has a more applied and practice
oriented nature. These context free concepts of social psychology are only of use in public
administration if they are incorporated in a public administration relevant context and
concepts. This first of all means that we gradually have to further translate and test the
findings in a real world public administration setting. Second, we have to establish how these
24
social psychology concepts interact with existing public administration concepts, such as
those from accountability, organizational theory or institutionalism.
This adaptation therefore should be reflected in the methods for establishing this: We will
need to conduct experiments to test all the theses formulated in this paper, as is common in
the field of social psychology, but applied in a public administration relevant context. The
usage of experiments is uncommon in the field of public administration, due to its
observational tendencies, but it is on the rise (Margetts, 2014). Most of the work regarding
accountability is on a theoretical or conceptual level (Brandsma & Schillemans, 2013) and
consists of typologies and the application thereof to various cases. Experimental research
contributes to achieving more predictive, formal theory and offers a higher external validity
when the results can be generalized to a real world setting (Koch & Wüstemann, 2014).
Experiments in accountability literature have thus far predominantly focused on the effects of
variations of accountability mechanisms on the agents. There is a comprehensive body of
experimental research on accountability and decision-making (see the overviews of Lerner &
Tetlock, 1999; Patil, Vieider & Tetlock, 2014; Koch & Wüstemann, 2014). Experimental
studies with the forum members as subject are, to my knowledge, unfortunately non-existent.
By using the experimental method we can use the wealth of formal theories that are developed
in social psychology. It allows us to provide a stronger internal validity for theories as
variation is created and controlled by the researcher (Margetts, 2011). The subjects are
exposed to this variation randomly and effect is observed after the fact, whereas commonly in
public administration variation is observed together with the outcome of interest. This
approach allows developing predictive theory based on causal inferences. Also, experiments
are better suited for gathering empiric data on the individual level. The focus on organizations
has brought as so much in accountability, but the relatively untapped underlying workings lies
with the individuals of whom these organizations consist.
25
The adaptation comes from employing field experiments. This as normal ‘experiments’ are
too artificial and do not involve the participants we are interested in, namely those in the field
of public administration. Also, exactly re-establishing the work that has already been done in
social psychology is rather fruitless. Instead, by employing the concepts translated into
relevant field experiments we can introduce them to ‘our’ settings and concepts, and thus
further public administration research. This allows us to find out how the typologies really
work on an individual level.
Conclusion
As presented here, there are established insights from attributional and attribution theory that
contribute to public accountability. Given attributional theory, we would expect that we could
explain more about the agent’s behavior that is currently missing in the typologies of public
administration.
The explanation for the forum’s behavior can be found on the bases of attribution theory. This
is helpful as it helps explaining the forum’s judgment. Kelley’s theory in particular explains
how a forum member attributes blame to either an agent, the target of the agent’s actions, or
particular circumstances based on three broad categories of information. By seeing an actor
acting in a consistent manner over time and in different instances, yet dissimilar behavior
from its peers, cause is most likely to attributed to the actor. The input of consistency,
distinctiveness and consensus information from Kelley’s model explains an attribution of
cause. Therefore, it forms a thus far missing link between first two and third stage in Bovens’
(2007) model of accountability.
26
Bibliography
Ahn, W. K., Kalish, C. W., Medin, D. L., & Gelman, S. A. (1995). The role of covariation
versus mechanism information in causal attribution. Cognition, 54(3), 299-352.
Alink, F., Boin, A., & ‘t Hart, P. (2001). Institutional crises and reforms in policy sectors: the
case of asylum policy in Europe. Journal of European Public Policy, 8(2), 286-306.
Beckman, L. (1970). Effects of students' performance on teachers' and observers' attributions
of causality. Journal of Educational Psychology, 61(1), 76-82.
Benjamin, L. M. (2008). Account space: How accountability requirements shape nonprofit
practice. Nonprofit and Voluntary Sector Quarterly, 37(2), 201-223.
Boers, I. & van Monfort, C. (2009). Raden van toezicht. In M.A.P. Bovens & T. Schillemans
(Eds.), Handboek publieke verantwoording (pp. 143-159). The Hague, The Netherlands:
Lemma.
Boin, A., 't Hart, P., & McConnell, A. (2009). Crisis exploitation: political and policy impacts
of framing contests. Journal of European Public Policy, 16(1), 81-106.
Boin, A., ’t Hart, P., & Sundelius, B. (2005) The Politics of Crisis Management. Cambridge,
UK: Cambridge University Press.
Borgida, E., & Nisbett, R. E. (1977). The Differential Impact of Abstract vs. Concrete
Information on Decisions1. Journal of Applied Social Psychology, 7(3), 258-271.
Bovens, M.A.P. (1998). The quest for responsibility: Accountability and citizenship in
complex organisations. Cambridge, UK: Cambridge University Press.
Bovens, M.A.P. (2007). Analysing and assessing accountability: a conceptual framework.
European law journal, 13(4), 447-468.
Bovens, M.A.P., 't Hart, P. (1996). Understanding Policy Fiascoes. New Brunswick, Canada:
Transaction.
27
Bovens, M. A. P., Brandsma, G. J., Thesingh, D., & Wever, T. (2010). Aan het pluche
gekleefd? Aard en achtergrond van het aftreden van individuele bewindslieden 19462009. Beleid en Maatschappij, 37(4), 319-340.
Bovens, M. A. P., ‘t Hart, P., Dekker, S., & Verheuvel, G. (1999). The politics of blame
avoidance: defensive tactics in a dutch crime-fighting fiasco. In H.K. Anheier (Ed.),
When things go wrong: organizational failures and breakdowns (pp. 123 – 147).
Thousand Oaks, CA, US: Sage
Bovens, M.A.P., Schillemans, T. and Goodin, R. E. (2014). Public accountability. In M.A.P.
Bovens, R.E. Goodin & T. Schillemans (Eds.), The Oxford Handbook Public
Accountability (pp. 1-20). Oxford, UK: Oxford University Press.
Brandsma, G. J., & Schillemans, T. (2013). The accountability cube: measuring
accountability. Journal of Public Administration Research and Theory, 23(4), 953-975.
Brändström, A., & Kuipers, S. (2003). From ‘Normal Incidents’ to Political Crises:
Understanding the Selective Politicization of Policy Failures. Government and
Opposition, 38(3), 279-305.
Breaux, D. A., Duncan, C. M., Keller, C. D., & Morris, J. C. (2002). Welfare reform,
Mississippi style: Temporary assistance for needy families and the search for
accountability. Public Administration Review, 62(1), 92-103.
Brown, J., & Weiner, B. (1984). Affective consequences of ability versus effort ascriptions:
Controversies, resolutions, and quandaries. Journal of educational Psychology, 76, 146158.
Brown, R., & Fish, D. (1983). The psychological causality implicit in language. Cognition,
14(3), 237-273.
28
Cheng, P. W., & Novick, L. R. (1990). A probabilistic contrast model of causal induction.
Journal of personality and social psychology, 58(4), 545-567.
Covington, M. V., & Omelich, C. L. (1979). Effort: The double-edged sword in school
achievement. Journal of Educational Psychology, 71(2), 169-182.
Cullen, F., Clark,G.A., Cullen, J.B., & Mathers, R.A. (1985). Attribution, salience, and
attitudes toward criminal sanctioning. Criminal Justice and Behavior, 12(3), 305–331.
De Vries, M. S. (2004). Framing Crises Response Patterns to Explosions in Fireworks
Factories. Administration & Society, 36(5), 594-614.
Deaux, K., & Emswiller, T. (1974). Explanations of successful performance on sex-linked
tasks: What is skill for the male is luck for the female. Journal of Personality and Social
Psychology, 29(1), 80-85.
Dubnick, M. J. (2014). Accountability as a cultural keyword. In M.A.P. Bovens, R.E. Goodin
& T. Schillemans (Eds.), The Oxford Handbook Public Accountability (pp. 1-20).
Oxford, UK: Oxford University Press.
Dubnick, M. J., & Frederickson, H. G. (2010). Accountable agents: federal performance
measurement and third-party government. Journal of Public Administration Research
and Theory, 20(suppl 1), i143-i159.
Fiske, S.T. & Taylor, S.E. (2007). Social cognition. New York, NY, US: McGraw-Hill.
Fontaine, G. (1974). Social comparison and some determinants of expected personal control
and expected performance in a novel task situation. Journal of Personality and Social
Psychology, 29(4), 487-496.
29
Försterling, F. (1989). Models of covariation and attribution: How do they relate to the
analogy of analysis of variance?. Journal of Personality and Social Psychology, 57(4),
615-625.
Fösterling, F. (2001). Atrribution: an introduction to theories, research and applications.
Hove, UK: Psychology Press.
Garvey, C., Caramazza, A. & Yates, J. (1976). Factors influence assignments of pronoun
antecedents. Cognition, 3, 227-243.
Gilbert, D. T., & Malone, P. S. (1995). The correspondence bias. Psychological bulletin,
117(1), 21-38.
Goldberg, L. R. (1981). Unconfounding situational attributions from uncertain, neutral, and
ambiguous ones: A psychometric analysis of descriptions of oneself and various types
of others. Journal of Personality and Social Psychology, 41(3), 517-552.
Grasmick, H.G. & McGill, A.L. (1994). Religion, attribution style, and punitiveness
toward juvenile offenders. Criminology, 32, 23–46.
Gundlach, M.J., Douglas, S.C., & Martinko, M.J. (2003). The decision to blow the
whistle: A social information processing framework. Academy of Management Review,
28, 107–123.
Grasmick, H. G., & McGill, A. (1994). Religion, attribution style, and punitiveness towards
juvenile offenders. Criminology, 32(1), 23-46.
Harris, L. T., Todorov, A., & Fiske, S. T. (2005). Attributions on the brain: Neuro-imaging
dispositional inferences, beyond theory of mind. Neuroimage, 28(4), 763-769.
Hart, P. T. (1993). Symbols, rituals and power: The lost dimensions of crisis management.
Journal of contingencies and crisis management, 1(1), 36-50.
Hewstone, M. (1990). The ‘ultimate attribution error’? A review of the literature on
intergroup causal attribution. European Journal of Social Psychology, 20(4), 311-335.
30
Hewstone, M., & Jaspars, J. (1987). Covariation and causal attribution: A Logical Model of
the intuitive analysis of variance. Journal of Personality and Social Psychology, 53(4),
663-672.
Hewstone, M., & Ward, C. (1985). Ethnocentrism and causal attribution in Southeast Asia.
Journal of Personality and Social Psychology, 48(3), 614-623.
Hilton, D. J. (1990). Conversational processes and causal explanation. Psychological Bulletin,
107(1), 65-81.
Hilton, D. J., & Jaspars, J. M. F. (1987). The explanation of occurrences and non-occurrences:
A test of the inductive logic model of causal attribution. British Journal of Social
Psychology, 26, 189–201.
Hilton, D. J., & Slugoski, B. R. (1986). Knowledge-based causal attribution: The abnormal
conditions focus model. Psychological review, 93(1), 75-88.
Hilton, D. J., Smith, R. H., & Kim, S. H. (1995). Processes of causal explanation and
dispositional attribution. Journal of Personality and Social Psychology, 68(3), 377-387.
Hood, C. (2002). The risk game and the blame game. Government and opposition, 37(1), 1537.
Jackson, C. L., & LePine, J. A. (2003). Peer responses to a team's weakest link: a test and
extension of LePine and Van Dyne's model. Journal of Applied Psychology, 88(3), 459475.
Jagacinski, C. M., & Nicholls, J. G. (1990). Reducing effort to protect perceived ability:"
They'd do it but I wouldn't.". Journal of Educational Psychology, 82(1), 15-21.
Jones, E. E., & Harris, V. A. (1967). The attribution of attitudes. Journal of experimental
social psychology, 3(1), 1-24.
31
Kassel, D. S. (2008). Performance, accountability, and the debate over rules. Public
Administration Review, 68(2), 241-252.
Kingdon, J. W.(2002) Agendas, alternatives, and public policies. London, UK: Longman.
Koch, C. & Wüstemann, J. (2014). Experimental analysis. In M.A.P. Bovens, R.E. Goodin &
T. Schillemans (Eds.), The Oxford Handbook Public Accountability (pp. 1-20). Oxford,
UK: Oxford University Press.
Koppell, J. G. (2005). Pathologies of accountability: ICANN and the challenge of “multiple
accountabilities disorder”. Public Administration Review, 65(1), 94-108.
Lee, Y. T., & Ottati, V. (1993). Determinants of In-Group and Out-Group Perceptions of
Heterogeneity An Investigation of Sino-American Stereotypes. Journal of CrossCultural Psychology, 24(3), 298-318.
LePine, J.A. & Van Dyne, L. (2001). Peer responses to low performers: An attributional
model of helping in the context of groups. Academy of Management Review, 26(1), 67–
84
Lerner, J. S., & Tetlock, P. E. (1999). Accounting for the effects of accountability.
Psychological bulletin, 125(2), 255-275.
Liden, R. C., & Mitchell, T. R. (1985). Reactions to feedback: The role of attributions.
Academy of Management Journal, 28(2), 291-308.
Lord, R.G. & Smith, J.E. (1983). Theoretical, informational, information processing,
and situational factor affecting attributional theories of organizational behavior.
Academy of Management Review, 8 (1), 50–60.
Lupson, J. (2007). A phenomenographic study of British civil servants' conceptions of
accountability. PhD Thesis. Cranfield University.
Major, B. (1980). Information acquisition and attribution processes. Journal of Personality
and Social Psychology, 39(6), 1010-1023.
32
Malle, B. F. (1999). How people explain behavior: A new theoretical framework. Personality
and social psychology review, 3(1), 23-48.
Mansbridge, J. (2014). A contingency theory of accountability. In M.A.P. Bovens, R.E.
Goodin & T. Schillemans (Eds.), The Oxford Handbook Public Accountability (pp. 2338). Oxford, UK: Oxford University Press.
Margetts, H. Z. (2011). Experiments for public management research. Public Management
Review, 13(2), 189-208.
Marks, G., & Miller, N. (1987). Ten years of research on the false-consensus effect: An
empirical and theoretical review. Psychological Bulletin, 102(1), 72-90.
Martinko, M. J., Douglas, S. C., Ford, R. C., & Gundlach, M. J. (2004). Dues paying: A
theoretical explication and conceptual model. Journal of Management, 30(1), 49-69.
Martinko, M. J., Douglas, S. C., & Harvey, P. (2006). Attribution theory in industrial and
organizational psychology: A review. International review of industrial and
organizational psychology, 21, 127-187.
McArthur, L.A. (1972). The how and what of why: Some determinants and consequences of
causal attribution. Journal of Personality and Social Psychology, 22, 171-193.
McArthur, L. Z. (1976). The lesser influence of consensus than distinctiveness information on
causal attributions: A test of the person-thing hypothesis. Journal of Personality and
Social Psychology, 33(6), 733-742.
McArthur, L. Z. (1981). What grabs you? The role of attention in impression formation and
causal attribution. In Social cognition: The Ontario symposium (Vol. 1, pp. 201-246).
Hillsdale, NJ, US: Erlbaum.
McMahan, I. D. (1973). Relationships between causal attributions and expectancy of success.
Journal of Personality and Social Psychology, 28(1), 108-114.
33
Mill, J.S. (1974). A system of logic ratiocinative and inductive. Toronto, Ontario, Canada:
University of Tronto Press. (Original work published 1840)
Miller, D. T. (1976). Ego involvement and attributions for success and failure. Journal of
Personality and Social Psychology, 34(5), 901-906.
Miller, D. T., Norman, S. A., & Wright, E. (1978). Distortion in person perception as a
consequence of the need for effective control. Journal of Personality and Social
Psychology, 36(6), 598-607.
Miller, D. T., & Ross, M. (1975). Self-serving biases in the attribution of causality: Fact or
fiction?. Psychological bulletin, 82(2), 213-225.
Naquin, C.E. & Tynan, R.O. (2003). The team halo effect: Why teams are not blamed
for their failures. Journal of Applied Psychology, 88(2), 332–340.
Nisbett, R. E., Caputo, C., Legant, P., & Marecek, J. (1973). Behavior as seen by the actor
and as seen by the observer. Journal of Personality and Social Psychology, 27(2), 154164.
Olsen, J.P. (2013). The institutional basis of democratic accountability. West European
Politics, 36(3), 447-473.
Olsen, J.P. (2014). Accountability and ambiguity. In M.A.P. Bovens, R.E. Goodin & T.
Schillemans (Eds.), The Oxford Handbook Public Accountability (pp. 1-20). Oxford,
UK: Oxford University Press.
Patil, S.V., Vieider, F. & Tetlock, P.E. (2014). Process versus Outcome Accountability. In
M.A.P. Bovens, R.E. Goodin & T. Schillemans (Eds.), The Oxford Handbook Public
Accountability (pp. 23-38). Oxford, UK: Oxford University Press.
Payne, S.L. & Giacalone, R.A. (1990). Social psychological approaches to the
perception of ethical dilemmas. Human Relations, 43(7), 649–665.
Peters, B.G. (2012). Institutional theory in political science. New York, NY, US: Continuum.
34
Pollitt, C. (2003). The essential public manager. New York, NY, US: McGraw-Hill
International.
Pruitt, D. J., & Insko, C. A. (1980). Extension of the Kelley attribution model: The role of
comparison-object consensus, target-object consensus, distinctiveness, and consistency.
Journal of Personality and Social Psychology, 40, 31-58.
Pyszczynski, T., & Greenberg, J. (1987). Toward an integration of cognitive and motivational
perspectives on social inference: A biased hypothesis-testing model. Advances in
experimental social psychology, 20, 297-340.
Ramsay, S., Gallois, C., & Callan, V.J. (1997). Social rules and attributions in the
personnel selection interview. Journal of Occupational and Organizational Psychology,
70(2), 189–203.
Romzek, B. S. (2000). Dynamics of public sector accountability in an era of reform.
International Review of Administrative Sciences, 66(1), 21-44.
Romzek, B. S., & Dubnick, M. J. (1987). Accountability in the public sector: Lessons from
the Challenger tragedy. Public Administration Review, 227-238.
Ross, L., Greene, D., & House, P. (1977). The “false consensus effect”: An egocentric bias in
social perception and attribution processes. Journal of experimental social psychology,
13(3), 279-301.
Ruble, D. N., Feldman, N. S., & Boggiano, A. K. (1976). Social comparison between young
children in achievement situations. Developmental Psychology, 12(3), 192-197.
Rudolph, U., & Főrsterling, F. (1997). The psychological causality implicit in verbs: A
review. Psychological Bulletin, 121(2), 192-218.
Schillemans, T. (2013). Moving Beyond The Clash of Interests: On stewardship theory and
the relationships between central government departments and public agencies. Public
Management Review, 15(4), 541-562.
35
Schillemans, T., & Bovens, M. (2011). The challenge of multiple accountability: Does
redundancy lead to overload? Accountable governance: Problems and promises, 3-21.
Schlenker, B. R., Britt, T. W., Pennington, J., Murphy, R., & Doherty, K. (1994). The triangle
model of responsibility. Psychological review, 101(4), 632-652.
Semin, G. R., & Fiedler, K. (1988). The cognitive functions of linguistic categories in
describing persons: Social cognition and language. Journal of Personality and Social
Psychology, 54(4), 558-568.
Semin, G. R., & Fiedler, K. (1991). The linguistic category model, its bases, applications and
range. European review of social psychology, 2(1), 1-30.
Silvester, J., Anderson, N.R., & Patterson, F. (1999). Organizational culture change:
An inter-group attributional analysis. Journal of Occupational and Organizational
Psychology, 72(1), 1–23.
Skelcher, C. (2010). Fishing in muddy waters: Principals, agents, and democratic governance
in Europe. Journal of public administration research and theory, 20(suppl 1), i161i175.
Stephan, W. G., & Gollwitzer, P. M. (1981). Affect as a mediator of attributional egotism.
Journal of Experimental Social Psychology, 17(5), 443-458.
Stone, D. (2002). Policy paradox: the art of political decision making. New York, NY, US:
WW Norton.
Storms, M. D. (1973). Videotape and the attribution process: reversing actors' and observers'
points of view. Journal of personality and social psychology, 27(2), 165- 175.
Sutton, R. M., & McClure, J. (2001). Covariational influences on goal-based explanation: An
integrative model. Journal of personality and social psychology, 80(2), 222-236.
Taylor, D. M., & Jaggi, V. (1974). Ethnocentrism and causal attribution in a South Indian
context. Journal of cross-cultural Psychology, 5(2), 162-171.
36
Weiner, B., Figueroa-Munoz, A., & Kakihara, C. (1991). The goals of excuses
and communication strategies related to causal perceptions. Personality and Social
Psychology Bulletin, 17, 4–13.
Weiner, B., & Kukla, A. (1970). An attributional analysis of achievement motivation. Journal
of personality and Social Psychology, 15(1), 1-20.
Weiner, B., Nierenberg, R., & Goldstein, M. (1976). Social learning (locus of control) versus
attributional (causal stability) interpretations of expectancy of success1. Journal of
Personality, 44(1), 52-68.
Weiner, B., Russell, D., & Lerman, D. (1979). The cognition–emotion process in
achievement-related contexts. Journal of Personality and Social psychology, 37(7),
1211-1220.
Wood, R.E. & Mitchell, T.R. (1981). Manager behavior in a social context: The impact
of impression management on attributions and disciplinary action. Organizational
Behavior and Human Performance, 28, 356–378.
Yesilkagit, K. (2009). Inspecties. In M.A.P. Bovens & T. Schillemans (Eds.), Handboek
publieke verantwoording (pp. 117-140). The Hague, The Netherlands: Lemma.
Zuckerman, M. (1979). Attribution of success and failure revisited, or: The motivational bias
is alive and well in attribution theory. Journal of personality, 47(2), 245-287.
37
Attributing cause in oversight: the role of consensus, distinctiveness, consistency
information
Public accountability is presumed to work via a three stage model: In the first two stages the
forum receives and later on demands information from an agent. In the third stage the forum
draws consequences for the agent on the basis of this information. In this paper we will test if
as suggested by attributional theory the type of information leads to a fixed tendency in causal
attribution. To this end we have devised a test based on this theory from social psychology
and put it to test with public professionals involved in oversight. The outcomes show that
variation in information about consensus, distinctiveness, and consistency of the agent’s
behavior does indeed influence the attribution of cause. However, unlike the preceding tests,
the now unsupervised participants were found to be more reluctant to give judgment except in
cases which the information should lead people to attribute cause to circumstances.
1. Introduction: accountability and attribution
Public administration literature regarding accountability tends to deal in typologies. These
describe mechanisms that make individuals and organizations accountable towards various
parties in various settings in the public sector. These vary from political to professional types,
from accountability concerning outcomes to processes. The accountability mechanisms are set
in lucid networks, or in rigid hierarchical manners. Also, the effects of accountability
configurations on organizations, such as gaps, or overloads, are part of public accountability
literature (For an overview of the field of public accountability see Bovens, Goodin &
Schillemans, 2014).
The most universally applicable typology from the field of accountability is the three stages
model by Bovens (2007). This model describes various phases in which an issue develops in a
relation between an agent and a forum. From normal routine till following up on
consequences for the agent stemming from judging it being at fault; the model describes the
38
most elementary process of accountability processes. In the first stage there is not yet an issue
between the agent and the forum. The agent goes about its normal routine and generates
information that the forum receives whilst doing so. This information is either as a byproduct
or generated deliberately by the agent. The second stage is initiated when the forum starts
actively seeking information about the agent’s activities and decisions. This can for example
be triggered by messages in the media or complaints of clients, but can also come about when
the forum itself becomes aware of a ‘gap’ in the information it has regarding the agent. The
agent’s response, or lack thereof, leads to the third stage. This stage consists of the forum
passing judgment on the basis of the information in the first two stages and the following
consequences for the agent.
However, the mechanisms of how a forum judges about the actions of an agent have been
shrouded in assumptions and are rarely made explicit. If mentioned at all, it is either naively
assumed that accountability mechanisms ‘just work’ because of the intention it has been
designed with. Or, it comes about by self-interest of the actors involved. Neither assumption
seems to capture how individuals of whom these forums consist come to their judgments. The
notion of ‘wrong is just wrong’ is an inadequate explanation, while various instances have
shown that gaming and framing out of self-interest does not give an adequate explanation
(Olsen, 2013; Schillemans & Busuioc, 2015). The logic of self-interest based attribution does
not all ways seem to apply, such as in the field of inspection and oversight. This, as their
presumed raison d’etre lies with attributing responsibility in an objective and neutral manner.
To explain how they seek to do this requires information based explanation, rather than a
motivational one.
The field of social psychology offers us attribution theory, which explains the attributions
individuals make under circumstances of uncertainty (Fiske, Taylor, 2007:143). Furthermore,
39
it is associated with being applicable to the attributions of cause of unexpected events and of a
negative nature (Kanazawa, 1992; Wong & Weiner, 1981). The theory shows that with this
type of attributions people do not tend to review a broad array of evidence, but rather hold on
to an available single sufficient explanation for the situation. It also explains how despite
inadequate information these attributions are made in a stable and therefore predictable
manner. This is fitting, as this is often applicable to situations in which the question of
responsibility in public accountability is posed. There are many consequences derived from
attribution that are in line with what we come to expect in the third stage of the accountability
model in public accountability. Frieze and Weiner (1971) for example demonstrated that the
attribution influences the success or failure people attach to the outcome.
Attribution theory has been well tested in various studies. The first conceptualization of
attribution theory was done by Heider (1944 in Fösterling, 2001). It consists of an explanation
for why people attribute cause based on the configuration of information they receive. It
prescribes that people make causal attributions on the basis of three types of information
about other people´s behavior. These types are consensus, distinctiveness, and consistency in
behavior. The variation of presence of these factors leads people to tend to hold either an
actor, the circumstances, or the subject of the actor’s actions to be responsible for the cause of
the established outcome. In this respect it would provide a prospect in understanding a part
the mechanisms that lead a forum to find an agent to be a cause, and thus responsible. This
question of consequences of information lies at the core of the three stages model as it hinges
between the first two stages and the third and thus explaining something of the thus far
assumed workings of accountability.
This leads to the following main question for this paper:
40
What is the influence of consensus, distinctiveness, and consistency information on the
attribution of cause in an oversight related public accountability setting?
After further elaboration – we will set apart the theory and the setting chosen to test the
operationalized concepts – we will establish whether or not the main hypotheses of causal
attribution hold in this context. Concretely, this means testing what influence configurations
of consensus, distinctiveness, and consistency have on the attribution of cause in a fictitious
case that is applicable to the context of the participants. This will show that theory from social
psychology theory holds in a public setting and offer some value in understanding the
underlying principles of accountability. Vice versa, this will be the first time that attribution
theory is applied in a field experiment. This means that – rather than artificial lab settings with
strong internal validity and participants consisting of undergraduate and graduate students –
this will be held amongst public professionals involved in oversight, such as regulatory
agencies and inspections. This will demonstrate whether or not these concepts have some
external validity as well.
41
2. Theoretical framework
2.1 Attribution theory
Attribution theory has a long linage. The earliest traces of these concepts can be found in
Mill’s method of difference (1840/1974). The basis of this theory stems from Heider (1958 in
Fiske & Taylor, 2007). He suggested that patterns of information were fundamental to
determination of causal attribution. A simple variation in presence of circumstances and
effects are the cause of finding that something has caused something to happen. If the effect
and the circumstance are present and in a second instant they both are not, and no third
instance occurs of the effect without the same circumstance, then this leads to establishing
cause and effect. This implies that multiple observations are needed: 1. presence and absence
of both effect and object; 2. the presence or absence of the effect with different states or
classes of objects and 3. the presence or absence of the effect with different persons
(Fösterling, 2001). To illustrate this abstract idea this example is given: When in one instance
a song is played and the person enjoys it, the song isn’t playing and the person lacks this
enjoyment in a second, and enjoyment does not occur under other circumstances, then this
leads to the conclusion that the song lead to enjoyment. This type of attributions is the socalled social causal attributions, and differs from ‘normal’ causal attribution. Here grounded
theory is used to explain the cause and is empirically confirmed by manipulating independent
variables. This is done so that people can confirm which effect these manipulations have on
the presences of the dependent variable .
Kelley (1967 in Fösterling, 2001) systematized Heider’s theory under the moniker of the
Covariation Principle, also known as the Kelley cube. The systematization contains the usage
of three classes of causes to explain the cause of events. These three classes of cause are actor,
entity or circumstances. The used categories of information regarding the behavior of the
actor are consensus, distinctiveness and consistency. Each of these categories are used when
42
establishing whether or not the cause of an effect lies with an observed or described person,
the entity it is interacting with, or the specific circumstances or moment in time. This is done
by looking at the covaration of the aspects that fall within the two categories. In this sense it is
attribution according to the method of difference. For example, if a person fails a task, but
achieves success with task 2 and 3 the effect (success) covaries with the task. If a person fails,
but others don’t with the same task it covaries with the person, and finally, if the person
succeeds with the task, but doesn’t other times with the same task, the effect covaries with the
circumstances or times. Kelley named these three covariations distinctiveness, consensus and
consistency, to indicate the absence of presence of entities, persons and circumstances over
time. This is very close to Heider’s original theory of variation in effect. This presumes that
people at first observe the presence or absence of the object, second the changes in the object
and third changes across persons (Fösterling, 2001: 48). Kelley suggested that there are three
ideal combinations of the informational categories. These tend to lead to one of three types of
attribution: the actor, the target of the actor and the circumstances or particular moment.
Circumstance attribution is noted to differ from the person and entity attribution as the former
refer to an actual independent variable, whereas circumstance does not attach an effect to a
specific variable (Grimm, 1980 in Fösterling, 2001). It is seen as a background factor rather
than a factor that covaries over time, because making this attribution assumes that multiple
observations have taken place, or at least were reported.
Various additions and changes to the Covariation model were suggested. These additions
mostly consist of an inclusion of further information that is used in attribution. These
revisions are the logical model (Hewstone & Jaspars, 1987), Pruitt and Insko’s (1980)
diamond model, the abnormal conditions focus model (Hilton & Slugoski, 1986), the
ANOVA model (Fösterling, 1989) and qualitative contrasts (Cheng & Novick, 1990).
Whereas Hewstone and Jaspars (1987), Pruit & Insko (1980) and Fösterling (1989), argue for
43
different configurations, Hilton and Slugoski (1986) do not. They instead argue that people
look for abnormal conditions. Their reasoning is that this is the way the Kelley Cube works:
consensus, distinctiveness and consistency information give information about whether or not
cases deviate from the usual. For example, the configuration of high consensus, low
distinctiveness and high consistency is known to cause conceptually unexpected attributions
(Fösterling, 2001). According to Kelley’s model this should not be the case as none of the
causes covary with the effect. The abnormal condition, however, does explain why this does
happen. Later refinements have moved away from general attributions, to cognitive and
neural mechanisms. The application of these theories lies outside the practical, as well as
having a limited value to public administration. In this paper we focus on early attribution as
it is well established and more applicable to our context. In the current state of the field,
research into knowing which information tends to lead to which attribution is more useful to
public administration than knowing which specific neurological processes take place.
McArthur (1972) was the first to formulize an experiment based on the Covariation principle,
and thus to empirically establish its validity. Findings based on McArthur’s model confirm
that an object or target stimulus is found for low consensus, high distinctiveness and
consistency (Hewstone & Jaspars, 1983; Orvis, Cunningham & Kelley, 1975). The same goes
for person stimulus. As predicted, this was highest for low consensus, low distinctiveness and
high consistency. This effect is less pronounced for circumstance as was predicted. The factor
seems to depend mostly on low consistency, as McArthur (1972) found that it occurred
conjoined with high consensus, low distinctiveness and low consistency and in high
consensus, high distinctiveness and low consistency. Orvis et al. (1975) found the same: they
noticed the same effect for three configurations, other than the ideal. They also found that
three-way interactions between the three factors are as not consistent as the model predicts.
Furthermore, it is remarkable that people do not collect information along the lines of
44
consensus, distinctiveness and consistency of behavior when given the opportunity (Fiedler,
Walther & Nickel, 1999). People instead draw conclusions from available information to
identify necessary and sufficient conditions for what has occurred (Hewstone & Jaspars,
1987). In general there are two known types of errors in attribution. The first errors are based
on simple miscalculation, but when attributions deviate systematically then we speak of a bias
(Fiske & Taylor, 2007). For example, a person or actor bias is consistently noticed. In the first
empirical test done by McArthur (1972) 82% made a person attribution in which the
covariance should lead to this conclusion. When the information for target was given the
attribution to the target was only 63%.
There are some other remarks regarding Kelley’s model and McArthur’s test. It should be
noted that both have various limitations. First, the model does not take into account
perceptions of intention (Malle, 1999). The model theorizes causal attribution, but does not
regard the observed actor’s intentions as part of it. This, however, favors the application in
public accountability. It is the perception of responsibility that seems to matter; the factor of
intentionality is of lesser importance. In public accountability there are many instances of
people being held responsible for events and outcomes that they did not intend to happen or
even had no personal control over (e.g. ministerial responsibility). This makes the theory
compatible with the varying notions of responsibility in public administration. In this case it
equates to the notion of responsibility as in being the cause. Second, in the proto-typical
operationalisation by McArthur, not making attribution is implied not to be an option (Hilton
& Slugoski, 1986 and Hewstone & Jaspars, 1987). Again, there are public settings where
refraining from judgment is not a default option. This is especially the case in the second
stage of accountability when the forum demands answers for what has come to pass (Bovens,
2007). When crises occur, something or somebody must be blamed for causing the crisis,
failing to prevent it, or inadequately responding to it (Bovens and ‘t Hart, 1996; Hood, 2002).
45
Third, it is suggested that the Kelley model is applicable in settings where causal information
is either missing or ambiguous. When asked to formulate an account, people primarily prefer
contextual causal information over information regarding consensus, distinctiveness, and
consistency (Ahn, Kalish, Medin & Gelman, 1995). Also, in public accountability settings it
is imaginable that causal information is not (sufficiently) available, but again despite this
lacuna, subjects have to formulate a (preliminary) judgment. On a related note, it is suggested
that Kelley’s model is more applicable in attributions of complex and interpersonal events
than for attributions in simple, impersonal events (Major, 1980). This is as well often the case
in public settings; it is characterized with multiple actors, variety of interpretations of facts,
and multi-causality. These limitations of the Kelley model fit the intended subject of public
accountability settings.
Next to these theoretical notes, there are also some methodological pointers. All most all
studies involving attribution thus far involved graduate students and took place in artificial lab
settings. The sample size varied; the majority has a range from 76 till 113 subjects. Four
larger studies contain sample sizes of 140 (Sutton & McClure, 2001), 161 (Hilton, Smith &
Kim, 1995), 384 (Pruitt & Insko, 1980) and 298 (Liden & Mitchell, 1985). The subjects are
all graduate or undergraduate students. It would be desirable from a public administration
perspective to replicate the experiment by applying the Kelley model on subjects that are
actual public professionals and using scenario's that are relevant to their context. If found
valid, it would strengthen the theory’s external validity. Particularly, it would do so in the
field we are interested in.
46
2.2 Proving grounds and the three stages model in practice: oversight by inspections and
regulatory authorities.
The use of Kelley’s model and the need to replicate the experiments is clear. However, the
three stages model is an abstract of various public accountability relations. Since we can’t
cover them all in this paper, we have chosen a field which has most quintessentially
professionalized the role of forum in the public sector: regulatory authorities and inspections.
In this field we will test the validity of attribution theory within public accountability. Dutch
examples of these organizations are inspection of education (Inspectie van het Onderwijs) and
inspection of healthcare (Inspectie voor de Gezonheidszorg). These inspections are
predominantly focused on organizations that fulfill tasks that to some degree belong to the
public sector. There are also those that are focused on the market. Such supervisory
authorities are authority financial markets (Autoriteit Financiële Markten) en consumer
market authority (Autoriteit Consument en Markt).
In broad lines these public organizations have three activities along the lines of the three
stages model. In the first and second stage: initiating oversight by programming work for a
longer period, prioritization on basis of signals, and risk analysis or complaints. Further tasks
are keeping oversight by gathering information, doing research on the basis of an agenda, but
also giving information about the method of oversight in terms of goals and methods. Last
stage consists of judgment and sanctioning. Here the inspection analyses the gathered data
along the lines of a regulatory framework. This leads to conclusions about the organizations
that fall under their supervision. If these are found to be unsatisfactory they can lead to
sanctioning (Yesilkagit, 2009). A broad divide can be made between two styles of relating to
the agent by the organization. This can be in a style of sanctioning, compulsion, coercion and
penalism. Or, they can opt for a relation based on compliance, conciliation, compromise en
remedialism (De Bruijn & Ten Heuvelhof, 2005). The activities of organizations with the
burden of control can be captured in two forms: First, upholding rules and legislation. This
47
instrument is limited as more detailed rules lead to more detailed and complex manners of
makings sure these are upheld. With increased complexity comes increased cost of inspecting
and regulation. It also disregards plurality of contexts and the risk that the rules are not fitting
to varying practices. Second is bureaucratization of the relation between inspector and
inspected. This is the increase of standardizations of procedures, obligations, reports and
documentation, or an increase of inspection and regulation or over-enforcement. As per usual,
the right context based fit needs to be found; too much leads to an accountability overload, too
little to an accountability gap.
The inspected are in turn known to employ various strategies for dealing with their inspectors
in case of offences (De Bruijn & Ten Heuvelhof, 2005). First is admitting, be it reluctantly or
partially. Second is to share the dilemma and decision-making with the inspector, making
them co-responsible. Another approach is to simply blame others such as superiors,
competitors, suppliers, customers or other governmental bodies. It can make promises, to
numb the inspection (regardless of whether they will be implemented or not), or anticipate
changes within the personnel of the inspection or their regime. It can go forum shopping:
selecting their own inspections as it befits them. Befriending, revolving door and lobbying are
other tactics to lessen the burden of inspection. Lastly, it can confront the definitions, rules
and regime of the inspection in the hope of finding external support and to overturn
unfavorable oversight.
Whatever type of oversight and whatever modus operandi the agents have, a cause needs to be
addressed after an undesirable outcome has occurred. This context is chosen for our
experiment as the position of inspections are less likely to be pre-determined on framing as in,
for example, a political context.
48
In the practice of oversight the scale of responsibility is predominantly put on the corporate
level. It is de facto the standard for regulatory authorities. Rarely is the individual addressed,
instead operations of the entire organization is seen as it were one actor. This means that by
personifying the corporation, the actions of all the individuals are reduced to that of this one
entity. It solves the so-called problem of many hands by having not to engage in identification
and verification on the lowest levels (Bovens, 1999: 53-58): the organizational levels suffices.
From the neo-classical view point in law and economics addressing the organization as such
is recommended. It can regulate its own conduct and address its members internally. In this
manner sanctions and risk of being caught cause the involved actors to refrain from socially
undesired conduct. The rational, bureaucratic structure of complex organizations, by division
of labor and specialization, hierarchy, delineated competencies and procedures, management
on documents makes entire organization easier to control than natural persons. This corporate
form of responsibility is, however, often extended (in political and legal sense) to natural
persons. Solely it would fall short in moral and pragmatic sense (Bovens, 1998: 73). The
morality problem of corporate accountability lies with the diffusion of it. Organizations have
no conscience in the usual sense like a natural persons does (Bovens, 1998: 66).
Organizations are designed to promote the motives that drive their objectives: maximization
of turnover, profit, market share, competencies or tasks are primary considerations and are put
above empathy. The norms an organization might have are not a substitute for feelings of pity,
guilt and empathy that a natural persons has.
This corporate responsibility also bears some pragmatic downsides: First, judging entire
organizations as an actor requires a good access to information about their actions and
decisions (Bovens, 1998: 64). This is often, however, hard to obtain for outsiders. This is
important both for formulating the rules and to trace the organizations factual course of affairs
(i.e. what is presented by the organization, did that really happen the way they describe it, and
49
where the figures and facts presented really the actual outcomes?). It can be difficult and
costly to gather the evidence needed to prove wrongdoing for an external party. These high
barriers lead almost naturally to a specialization of specialized controlling bodies and a
symbiosis with those they are supposed to regulate. They speak the language, share
knowledge and even personnel might be exchanged (Finney & Lesieur, 1982: 281). This way
there is no guarantee that external norms and regulations will have an impact on the
organization (Bovens, 1998: 62). This is a structural problem as the incentive to legally
comply is only maintained at the hierarchical top. The subdivisions and lower levels are given
other goals that come primarily, above this (Braithwaite, 1985 in Bovens, 1998). Legal
sanctions can be seen as a risk in economic terms, rather than a reputational issue (Stone,
1975 in Bovens, 1998). Also, not all layers of the organization might communicate
sufficiently. Due to complex organization in specialized areas the diffusion of information can
be limited even within the organization. Complex organizations might also not be that stable
and consistent, due to changing membership. This also impacts learning capabilities (Bovens,
1998: 63). The pragmatic problem is furthered due to ex post control. The instruments can
only keep them in check after the event. Damages, fines, judicial orders, shutdowns, or forced
reorganizations are after the fact; After people notice damages that justify taking such actions
(Bovens, 1999: 60). The best they can do is stopping the continuation of practices. Another
associated downside of this form of responsibility stems from the ex-post side effects: the
organization is declared bankrupt or disbanded. These consequences often involve fall out for
innocent parties such as employees, clients or customers and suppliers. Imposing fines on
public institutions will mostly be meaningless as it will lead to a budgetary deficit. In turn,
these deficits will impact the services the clients receive (Torring, 1984: 153-158 and Vogel,
1986: 16 in Bovens, 1999: 69).
50
So far we have discussed the theoretical relevance of causal attribution theory for public
accountability. We have concluded this overview of the setting in which this test takes place
and upon which the case is based: people involved in oversight in inspections and regulation,
pinpointing responsibility in a fictitious case involving an organization as actor. For the
following empirical component I will elaborate the hypotheses and the conducted field
experiment for establishing the validity of this theory in a setting relevant to public
accountability.
We will use the archetype of attribution for the survey experiment for this article as
formulated by Kelley (1967) and McArthur (1972). This consists of three types of possible
attributions of cause on the basis of three information components. Whereas the actors in most
previous tests are individuals, we have an organization as an actor. This study does not test
the `full´ grid of causal attribution, i.e. all possible variations in presence of the factors of
consensus, distinctiveness, and consistency as this has already been done in many previous
articles. We will rather take the three archetypical configurations for an actor, target, and
circumstance attribution and test these applied to the context of oversight.
The first configuration tends to actor attribution, hence the name actor configuration. This
attribution is made when information shows the actor’s behavior differs from the behavior of
other actors. His behavior is met with low consensus amongst observations of peers.
Secondly, the behavior of the actor is the same in instances where the actor interacts with a
different subject. Thus, the observer notes that the actor’s behavior does not just coincide with
the instances involving that particular subject. Third, the actor shows consistency in behavior
over time. This gives the first of three ideal configurations, which in this case should lead to
the highest score for actor attribution. If we were to translate this to a setting relevant to a
public setting, we could formulate that an agent has shown not being able to complete a task
as did other agents. Additionally, the agent did not only fail completing this task, but has
51
failed to complete other tasks as well. Lastly, not only did the agent fail in a single instance,
but he failed over time in multiple instances. According to attribution theory, if we were to
give respondents this configuration of information, the perception of responsibility for the
situation should be substantially higher for agent. This then leads to the first hypothesis:
Hypothesis 1: A failure of agent to complete a task described with low consensus, low
distinctiveness and high consistency leads to a higher finding of cause with the agent
compared to the other configurations.
The second configuration is the subject attribution. This attribution is made more often when
the actor shows behavior similar to its peers. A high distinctiveness is observed, meaning that
the behavior of the agent is dissimilar in interaction with other subjects. Lastly, over time this
behavior is observed in multiple instances with the same subject. This is the second ideal type
of information which in this case should lead to putting the cause predominantly with the
subject. Again, applying this configuration leads to an agent failing, as well as other agents.
The agent did succeed in completing different tasks, however the failure to complete this
specific task is observed in multiple instances over time. The hypothesis then is:
Hypothesis 2: A failure of an agent to complete a task described with high consensus, high
distinctiveness and high consistency leads to a higher finding of cause with the task compared
to the other configurations.
A third ideal type is formed when an actor is found to act dissimilar form its peers. It behaves
differently in instances with different subjects and also behaves dissimilar in multiple
instances with the same subject. This configuration should lead participants to find the cause
in the particular circumstances of the moment in which the event took place. By abducting
this last ideal type we should come to a formulation in which both the agent and its peers fail
52
a task. This is, however, only observed with this case, not in others, and this is only observed
in one instance. The last hypothesis is then:
Hypothesis 3: A failure of an agent to complete a task described with low consensus, high
distinctiveness and low consistency leads to a higher finding of cause with the particular
circumstance compared to the other configurations.
3. Method: proposed materials and analysis
An unsupervised computer based survey was designed to test the hypotheses. This was
deployed in a group on the professional social network LinkedIn: “Toezicht, opsporing en
Handhaving” (regulatory authority, detection and control). This is a closed community for
public professionals holding functions related to these fields. Consisting of 6,972 members,
the group is used to inform members of changes within the field, to exchange ideas and pose
practice related questions. Via a post in this group they were asked to participate in the
survey. In return they could participate in a draw for a voucher of an online store. The
participants from this group fit well as representatives involved the type of public
accountability relations we are interested in: oversight.
These real-world subjects consist of practitioners that are representative for employees in a
bureaucratic-legal setting. This test consisted of 147 participants of whom 41 women, 106
male. The average age of the participants was 48,73 (SD=11.19) years old. 96 participants
indicated that they held a job which was related to inspection and oversight, 49 indicated they
did not. 6 participants were unsure. The highest enjoyed educational levels of the participants
were as follows: 4 had completed elementary school, 5 completed secondary education, 21
intermediate vocational training (Dutch: MBO), 61 higher professional education (Dutch:
HBO), 51 academic education (Dutch: WO) and 4 post academic education (PhD or
specialization). Those that indicated that they held a supervisory job indicated, for example,
that they were a senior environmental inspector, head of inspection, but also involved in
53
enforcement of licenses and permits. Those participating that indicated that they did not hold
such a job, held a job that was often related to the field such as researcher, alderman or legal
advisor.
From the accessible papers containing empirical studies of causal attribution, the method
generally follows the lines of McArthur (1972). This is either by using the same items, e.g.
Ruble & Feldman (1976), Harris, Todorov & Fiske (2005). But, the majority of studies make
adaptations while using the same prescribed configurations of consensus, distinctiveness and
consistency. This survey experiment was conducted along these lines.
As stated, the participants were given a computer based unsupervised survey in Dutch (see
Appendix A: Materials). After a short introductory text regarding the study, we asked the
participants to indicate whether or not they held a function which involved oversight and
inspection, and if so, if they could indicate their exact job title. After this page they were
presented with questions involving their age and sex. The next page asked the participant to
indicate their highest level of education. After these background questions the participants
were presented with a screen with the instructions for the experiment. This screen noted that
the participants were about to receive limited information about a case and that after reading
they had to answer some questions. After moving on to the next screen, the participants
randomly were assigned to one of four cases. These were operationalizations of the three ideal
types of attribution for actor, target or circumstance. The fourth case was control with no
additional information. 35 participants were assigned to the actor configuration of
information, 35 to task, 37 to circumstance, and 37 control.
Regarding the variables, the subjects first were asked to fill in control variables (job type, age,
their gender and education). These served as control variables. The variables job type, gender
and education were dummy coded with respectively not holding a job related to oversight,
54
men, and low education as baselines. The educational levels were put into three categories,
high, medium and low. Then a generic negative accomplishment was given (in Dutch)
consisting of the common causal object-verb-target construction: “De organisatie voltooide de
taak niet” (the organization did not complete its task). This statement was followed by
information according to the person, target or circumstances manipulations of consensus,
distinctiveness and consistency. These assigned groups were used as three dummy variables.
The baseline for these assigned groups was the control group with no additional information.
Then the subjects are asked to infer causality for the given event. The options were (a) “the
organization” (b) “the task” and (c) “the particular circumstances”. For each of these options
the participants were asked to score these on a 0 – 100 scale. These three scores form the
dependent variables: actor score, task score and circumstance score. Additionally, we asked
the respondent to give their account of what might have happened in the given scenario:
“What, based on the limited information, did according to you, to your best knowledge,
happen” in Dutch. A couple of lines were provided to the participants to fill out. This served
as a manipulation control; it gave a qualitative insight in the interpretation of the information
by the participants. Answering this question was optional. In total 172 respondents started
with the questionnaire. Only 96 respondents completed it. 144 made it until the description of
the cases, while 48 participants dropped out at the moment of judgment.
To test the hypotheses multiple-regressions were applied to the data generated from the
experiment in three sets of three models. The first model of each set contains only control
variables: gender, age, type of education, and whether or not the respondent held a position in
which he or she is involved in regulation of some kind. The second model contains only the
concepts from the theoretical framework. Those are the three ideal typical types of
information given that should ideal typically lead to either the actor attribution, the subject
attribution or the circumstance attribution. The last model contains all variables from both
55
previous models; this is the complete model. For each model OLS and bootstrapped
regressions were used. After finding that the normality assumptions were violated to some
degree for some regressions after visual and statistical tests on the residuals, have we decided
to include the bootstrapped standard error values (see S-W test in the regression table notes).
By using the bootstrapped regressions we still were able to get an idea of the generalizability
of these findings, despite this problem with the sample data for some regressions (Efron &
Tibshirani, 1993).
56
4. Data
4.1 Descriptives
In this part we will present the data drawn from the survey. First, we will look at the scores
for the actor, the target, and the circumstances per factor. Actor score for men was 58.74 out
of 100 (SD=23.22) for women 57.59 (SD=28.16). Task was 37.81 (SD=28.99) for men,
women scored lower with 29 (SD=21.67). Circumstances returned 52.74 (SD=27.96) for men,
while women scored a mean of 42.22 (SD=28.41).
Second, for actor score we see a lower number for people holding functions involving
oversight and inspection. They scored 56.20 (SD=25.14). Participants not holding such a
function scored 68.88 (SD=21.40). Lastly, those who weren’t sure scored 41.5 (SD=31.82).
For the task score we see on average a 36.87 (SD=28.79) for people involved in inspection,
30.16 (SD=23.32) for those who don’t. While the undecided gave 47 (SD=18.38). For the
circumstances score the first group gave 51.61 (SD=28.39). The second group 49.36
(SD=28.40) and the third 32.50 (SD=17.68).
Third, for the factors of education we see a mean score for the actors of 65.33 (SD=13.61) for
secondary education, intermediate vocational training scored 60.86 (SD=29.86). Higher
vocational training scored 57.68, (SD=23.91), academic 58.51 (SD=25.36) and Post academic
46.67 (SD=15.27). For task score secondary scored 43.33, (SD=36.22), intermediate
vocational 29.21, (SD=25.28). Higher vocational scored 39.53 (SD=27.59), academic 28.17
(SD=24.95) and post academic 68.67, (SD=16.44). Lastly, for circumstances score secondary
scored 56.67 (SD=18.15), intermediate vocational 57.21 (SD=35.81), higher vocational
scored 46.03 (SD=26.60), academic 51.66 (SD=28.64) and post academic 58.33 (SD=14.43).
57
Table 4.1: actor score per information configuration
Configuration
Actor score
Actor configuration
76.65 (SD=22.70)
Task configuration
62.5 (SD=19.63)
Circumstance configuration
49.32 (SD=22.55)
Control configuration
52.18 (SD=24.64)
So far we have not seen remarkable differences in scores across the groups that aren’t
associated with small n outliers. This is especially unsurprising giving the large standard
deviations. However, if we turn to the configuration of information we clearly see a difference
in scoring amongst the four types of information given. The participants with the actor
configuration gave the highest scores to the actor. They saw the actor as the most likely cause
for what has happened due to the configuration of consistency, distinctiveness and consensus
they were given. Participants with other configurations saw the actors less likely as the cause.
The attributing cause to the actor is reflected in the potential causes we asked the participants
to formulate. For example: “the organization got a task which – perhaps due to circumstances
– it wasn’t able to execute.” (participant scores: organization: 80, task 1, circumstances 20).
Table 4.2: Task score per information configuration
Configuration
Task score
Actor configuration
35.05 (SD=24.46)
Task configuration
51.45 (SD=30.38)
Circumstance configuration
26.68 (SD=26.25)
Control configuration
34.32 (SD=18.82).
For task score we see again a higher mean score for the designated configuration, in line with
the hypotheses. The participants with configurations for actor, circumstance and control gave
58
lower scores, indicating that they saw the task less likely to be the cause. An example of an
explanation a participant gave: “The organization thinks the task is irrelevant for
organizational goals or potentially unnecessary cumbersome.” (participant scores:
organization 80, task 100, circumstances 85).
Table 4.3: Circumstance score per information configuration
Configuration
Circumstance score
Actor configuration
44.40 (SD=29.36)
Task configuration
40.20 (SD=25.50)
Circumstance configuration
69.15 (SD=24.31
Control configuration
37.14 (SD=19.96)
Last attribution, the circumstances show the same predicted pattern: Only participants with a
circumstance configuration clearly attributed most of cause to circumstances. An elaboration
from a participant from this group stated: “External factors/circumstances have led to a
divergence in the actions taken by the organization.” (participant scores: 50 actor, 50 task,
and 100 circumstances).
4.2 Regression
In this section we will look at the results of the regressions. As stated in methodology, for
each of the three types of scores – actor, target and circumstance – three models were tested.
The first model only tests for the control variables. The second model tests the four types of
configuration of consensus, distinctiveness and consistency information, i.e. actor, target and
circumstances configurations. The last model tests the complete model combining first and
second model.
59
Gender
Model 1: control variables
(n = 96)
Model 2: experimental
variables (n = 96)
Model 3: full model
96)
-2.048
-
-2.231
(6.113/6.363)
Age
-.049
(5.749/5.408)
-
(.233/.195)
Regulatory function
-8.859
-6.483
-
-8.911
-
-10.057
-
-
-.691
(12.588/7.903)
24.468***
25.480***
(9.956/7.087)
(7.270/7.357)
10.318
10.932
(6.956/6.987)
(7.388/7.264
-2.858
-1.998
(6.161/6.430)
(6.749/6.978)
76.370***
52.182/***
63.046***
(17.585/11.616)
(4.800/5.205)
(16.464/10.127)
Adjusted R2
-.034
.159
.129
F
.475
7.002***
2.560**
Task configuration
Circumstance configuration
Constant
-
.585
(12.512/6,537
(13.369/7.634)
Actor configuration
6.323
(13.620/9.966)
(13.359/6.995)
Academic education
-6.493
(5.472/5.631)
(14.328/9,591)
Higher education
-.147
(.216/.193)
(5.829/5.971)
Medium education
-
-
(n =
Table 4.4: Actor score. Notes: * p < 0.1, ** p<0.05; *** p < 0.01 for bootstrapped regression. Displayed values are unstandardised
regression coefficients (normal and bootstrapped standard errors in parenthesis). For model 1: S-W test on distribution residuals p > .05;
3.13% of cases outside 2 st. dev.; DFBeta < 1, Cook’s max <1; Durbin-Watson = 1.906; average VIF = 3.419, none > 10; no
heteroscedasticity detected visually. For model 2: S-W test on distribution residuals p > .05; 8.33% of cases outside 2 st. dev.; DFBeta < 1,
Cook’s max <1; Durbin-Watson = 1.815; average VIF = 1.55, none > 10; no heteroscedasticity detected visually. For the model 3: S-W test
on distribution residuals p > .05; 4.16% of cases outside 2 st. dev.; DFBeta < 1, Cook’s max <1; Durbin-Watson = 1.74; average VIF =
2.966 , none > 10 ; no heteroscedasticity detected visually.
60
Looking at table 4.4 we see that for the actor score none of the control variables show a
significant effect on the score to which degree the organization is to blame for not fulfilling its
obligation. The model is – as shown by the R2 score – extremely poor. Model 2 contains the
attributional factors as sole independent factors. Shown is that, as predicted, given the
organizational attribution information leads to a significantly higher score on the degree to
which the organization is responsible for the situation (β=.406, B=24.47, p<.001). The other
configurations (task and circumstance) did not contribute significantly. This means that the
first hypothesis is not rejected. This model explains about 16% of the variance in scores.
Model 3 contains both control variables and the attributional factors. The model explains less
of the variance in the scores for organizational blame as R2 decreases. Also, organizational
information remains the sole significant factor (β=.423, B=25.48, p<.001).
61
Model 1: control
variables (n = 96)
Model 2: experimental
variables (n = 96)
Model 3: full model
(n = 96)
Gender
-7.357
-
(6.616/6.197
Age
.300
(6.523/5.918)
-
(.252/.282)
Regulatory function
2.550
-23.832
-
-10.752
-
-17.928
-
-
-12.588
(12.588/15.801)
.732
-2.862
(8.091/7.410)
(8.248/7.886)
17.132**
13.273
(8.091/7.777)
(8.382/8.712)
-7.642
-10.290
(7.166/6.229)
(7.657/6.629)
36.150*
34.318***
34.385*
(19.033/21.838)
(5.583/4.152)
(20.136/20.663)
Adjusted R2
.020
.081
.093
F
1.330
3.775**
2.088**
Task configuration
Circumstance
configuration
Constant
-
-7.375
(14.195/15.942)
(14.470/17.136)
Actor configuration
-19.664
(15.452/15.973)
(14.460/17.401)
Academic education
4,098
(6.208/6.279)
(15.508/17.492)
Higher education
.264
(.246/.272)
(6.309/5.620)
Med education
-8.244
-
-
Table 4.5: task score. Notes: * p < 0.1, ** p<0.05; *** p < 0.01 for bootstrapped regression. Displayed values are unstandardised regression
coefficients (bootstrapped standard errors in parenthesis). For the model 1: S-W test on distribution residuals p < .05; 2.08% of cases outside
2 st. dev.; DFBeta < 1, Cook’s max <1; Durbin-Watson = 1.974; average VIF = 3.418 , none > 10 ; no heteroscedasticity detected visually.
For model 2: S-W test on distribution residuals p < .05; 2.08% of cases outside 2 st. dev.; DFBeta < 1, Cook’s max <1; Durbin-Watson =
2.024; average VIF = 1.533, none > 10; no heteroscedasticity detected visually. For model 3: S-W test on distribution residuals p > .05;
2.08% of cases outside 2 st. dev.; DFBeta < 1, Cook’s max <1; Durbin-Watson = 1.922; average VIF = 2.966, none > 10; no
heteroscedasticity detected visually.
62
Again, for model 1 we see no significant factors in the control variables for explaining to
which degree the task contributes to the given outcome and the model in total explains little of
the variance. In model 2 we see, again as hypothesized, that task configuration leads
significantly to scoring higher in task attribution (β=.256, B=17.13, p<.05). The second
hypothesis is as well not rejected. However, the significance is less strong, as is the value of
the score and the R2. This means that the effect of task configuration on task attribution is less
strong compared to actor configuration on actor attribution. This is visible as well for the full
model: the task attribution even becomes insignificant, although barely so.
63
Model 1: control
variables (n = 96)
Model 2: experimental
variables (n = 96)
Model 3: full model
(n = 96)
Gender
-5.898
-
(6.989/6.826)
Age
-.080
(6.326/5.981)
-
(.266/.269)
Regulatory function
2.664
.129
-
-9.729
-
-3.794
-
-
-18.497*
(13.850/10.916)
7,264
6.655
(7.664/7.455)
(7.999/7.924)
3,064
3.508
(7.664/7.166)
(8.129/7.306)
32.011***
33.163***
(6.787/5.907)
(7.426/6.563)
59.785**
37,136***
62.152**
(20.107/15.845)
(5.288/4.136)
(18.115/15.821)
Adjusted R2
-.030
.223
.197
F
.541
10.085***
3.586***
Task configuration
Circumstance
configuration
Constant
-
-20.871**
(13.767/10.140)
(15.286/10.477)
Actor configuration
-15.694
(14.986/13.288)
(15.275/10.078)
Academic education
-3.214
(6.021/6.763)
(16.382/13.792)
Higher education
-.095
(.238/.245)
(6.665/6.446)
Med education
-.593
-
-
Table 4.6: circumstance score. Notes: * p < 0.1, ** p<0.05; *** p < 0.01 for bootstrapped regression. Displayed values are unstandardised
regression coefficients (bootstrapped standard errors in parenthesis). For the model 1: S-W test on distribution residuals p > .05; 1.04% of
cases outside 2 st. dev.; DFBeta <1; Cook’s max <1; Durbin-Watson = 1.91; average VIF = 3.419 , none > 10 ; no heteroscedasticity
detected visually. For model 2: S-W test on distribution residuals p > .05; 1.04% of cases outside 2 st. dev.; DFBeta <1; Cook’s max <1;
Durbin-Watson = 1.61; average VIF = 1.555, none > 10; no heteroscedasticity detected visually. For model 3: S-W test on distribution
residuals p >.05; 2.08% of cases outside 2 st. dev.; DFBeta <1; Cook’s max <1; Durbin-Watson = 1.64; average VIF = 2.966, none > 10; no
heteroscedasticity detected visually.
64
For the last attribution, that of circumstances, we see again no significant factors in the model
containing the control variables. In model 2 we see that, as predicted, the circumstances
configuration attributes significantly to the score attributional for circumstances (β=.547,
B=32.11, p<.001). The third hypothesis is not rejected and the model explains 22% of the
variance. For the full model we see an interesting effect as for education both higher (β=-.367,
B=-20.87, p<.05) and academic groups (β=-.323, B=-18.50, p<.1) become significant factors,
next to the informational configuration factor for circumstance (β=.567, B=33.16, p<.001).
The model in total, however, explains less variance compared to the model containing only
the attributional factors.
4.3 Additional tests
As stated previously, we did notice a drop out of participants. Of the 172 participants that
started only 96 gave scores for the various causes after reading the cases. This might be due to
the unsupervised nature of this test or the abstract and context-free cases presented. All
previous studies were all supervised in some manner and had no reported drop out. When
controlling for the previously used independent variables around 40% of the participants
stopped for all but one configuration of information. In the groups that were assigned to the
cases with configurations of information for control (40.5%), target (42.9%) and actor
(42.9%) this occurred, but not for the circumstance configuration. Here only 8.1% dropped
out. It was found that the odds of continuing and attributing causes were 8.23 times higher for
people who were presented with the circumstantial configuration compared to the other
configurations (Chi square (1), 14.258 p <.001, Cramer’s V=.315).
65
5. Findings, limitations, and discussion
5.1 Findings
The results show that people do differ the attribution of cause due to a variety in consistency,
distinctiveness, and consensus information; the three hypotheses based on these three idealtypes were not rejected. By changing these three factors people do tend attribute cause
differently. As hypothesized the three configurations shifted the degree of attribution. First,
when an actor shows consistent behavior in the same and different tasks while other actors do
not show this behavior (actor configuration) then the actor is seen as most likely cause. The
second is the task configuration. In this case the actor shows the same behavior with the same
task, like other actors, but it varies with different tasks. This configuration indeed shifted the
cause to the task, although less pronounced when other factors are taken into consideration.
Lastly, circumstances were most likely to be seen as a cause when the actor had shown
different behavior over time, differed from different tasks and other actors behaved similar.
Thus, here as well did the configuration of consistency, distinctiveness and consensus
influence the finding of cause.
Only for circumstances do we see a significant result for one of the control variables.
Education, both university and vocational, leads to a higher finding of circumstances as a
cause, but interestingly enough only in the model in which attribution information is included
in the model. There is, however, no significant influence of age, gender, or even whether or
not the person held a function related to inspection and regulation.
Unexpectedly, the results show an unpredicted outcome that has not been recorded thus far in
similar studies. Many participants dropped out at the moment we asked them to attribute the
degree of cause. As to what might have caused this we can only speculate as we did not
record people’s reasons for dropping out. However, data seems to indicate that people are
reluctant to judge on the basis of the provided information except for the cases where the
66
configuration leads to attribution of circumstances. The odds of continuing were significantly
higher for the group with the circumstantial information. This might indicate that people are
more at ease to attribute cause to circumstances when presented with this information. For the
people who did score the causes, we can confirm the main theses of attribution theory: people
do attribute cause on the basis of variety in consensus, distinctiveness and consistency
information.
The data also shows that this general idea from social psychology in this format applicable to
the public sector employees involved in inspection and regulation. It shows as well that
participants treated the actor as an organization; in the same manner as an individual in
previous studies. This supports the notion that people seem to treat organizations if they were
a person regarding organizational responsibility. Also, by leaving out questions regarding
perception of intentionality on part of the actor we have conceptualized responsibility in line
with Bovens’ (1998) connotation of responsibility as cause. Adding intentionality might be
useful as the consequent perceptions for locus of causality for internal causality (ability,
effort) differs from the external (chance, task difficulty).
5.2 Limitations
The results of this paper do, however, warrant some limitations. First, there is the mentioned
issue of a high percentage of respondents dropping out. 44% of the participants did not
proceed to giving scores. This makes the outcome unreliable as we do not know what effect
the configuration had for the scores of these participants. This high percentage drop out is not
reported in previous studies. These used a supervised lab experiment setting, unlike an
internet based survey as used here. It would be recommendable for a follow-up study to look
into both the effects of the method as into whether or not different configurations incite not
judging and dropping out.
67
As interesting as the findings are as a preliminary step in linking the first two stages to the
third of the accountability model, these findings are made on the basis of an in public
administration terms relatively context-free case. This is a strength of this test; it counts
towards some external validity. Yet, its conclusions should as well been seen in the light of its
limitations. The empirics here only involve findings in the micro-scale (the individual), have
no pre-text and no previous or interaction afterward of any kind with the participant. On the
one hand these additions of context are warranted by social psychology. There are concepts
that Kelley (1972) calls causal schemata which are used for attribution as well. These
attributions are based on Mill’s (1840/1974) method of agreement rather than difference; they
are based on prior knowledge and create different assumptions about the causes and effects.
This is not just true for attributions based on different assumptions; for the attribution type
studied here concepts such as inter-group versus outer-group, salience, internal sources of
cause versus external are just a few of the many known concepts to influence the perception
of cause from social psychology.
However, it could be argued as well that the addition of context would be redeeming from a
public administration point of view. Next to the more practice oriented nature of our field,
there are many concepts that indicate different types of accountability relations and settings.
These as well will surely have an influence on the perceptions of cause and the consequent
outcomes thereof. This alternative theoretical view sees accountability as a bridging element
between individual and social environment (Lupson, 2007; Mansbridge, 2014). This view
assumes that people seek approval, instead of maximizing their interest. Choices in this view
are based on logic of appropriateness, rather than the logic of consequences (Olsen, 2013 &
2014). Therefore specifics of the social environment should be taken into account in follow up
studies.
68
For each of these recommendations more in-depth and smaller scope studies would be
recommendable. We could look into how specific members of organizations in such settings
come to accountability for each of these concepts: What additional information do they use
for judging? Under which conditions are their judgments influenced? When do they deviate
from the baseline?
5.3 Conclusion
For now, this study has demonstrated a stable individual attribution in an instance of a case
with no previous knowledge and without referral to a third party. This is the first time causal
attribution theory has been applied to participants involved in a public administration relevant
context. Given the broad applicability of these three types of behavior, these findings form a
step in adding empirics to what was mainly shrouded in assumptions: linking the core
processes of public accountability. The three stages model (Bovens, 2007) presumes that the
forum passively receives information in the first stage of an issue, actively gathering
information and starts questioning the agent in the second. In the third stage the forum passes
their verdict and the agent undergoes the consequences thereof. Kelley’s attribution theory
(1967 in Fösterling, 2001) has proven here to be a linkage between the first to stages and the
third. It describes three categories of information about the agent (consistency, distinctiveness
and consensus regarding agent behavior). The configuration of the information has shown to
influence the degree to which the respondents felt the actor, the assigned task, or the
circumstances were the cause of failing to complete the task. Finding that this attribution
theory holds leads to the first step in formalizing the effects of information on the findings of
a forum. By furthering inquiry in this area we can continue to unravel how accountability
truly works and whether this is as rational as the typologies from public accountability make it
seem to be. Shown is that findings are drawn from less than perfect information, that the
69
attribution of responsibility is predictable by the configuration of this information, and that
some configurations of information seem to deter people from judging.
70
Bibliography
Ahn, W. K., Kalish, C. W., Medin, D. L., & Gelman, S. A. (1995). The role of covariation
versus mechanism information in causal attribution. Cognition, 54(3), 299-352.
Bovens, M.A.P. (1998). The quest for responsibility: Accountability and citizenship in
complex organisations. Cambridge, UK: Cambridge University Press.
Bovens, M.A.P. (2007). Analysing and assessing accountability: a conceptual framework.
European law journal, 13(4), 447-468.
Bovens, M.A.P., Hart, P. 't (1996). Understanding Policy Fiascoes. New Brunswick, Canada:
Transaction
Bovens, M.A.P., Schillemans, T. and Goodin, R. E. (2014). Public accountability. In M.A.P.
Bovens, R.E. Goodin & T. Schillemans (Eds.), The Oxford Handbook Public
Accountability (pp. 1-20). Oxford, UK: Oxford University Press.
Cheng, P. W., & Novick, L. R. (1990). A probabilistic contrast model of causal induction.
Journal of personality and social psychology, 58(4), 545-567.
De Bruin, H., ten Heuvelhof, E. (2005). Handhaving: het spel tussen inspecteur en inspectee.
Utrecht, The Netherlands: Lemma.
Efron, B., & Tibshirani, R. (1993). An introduction to the bootstrap. London, UK: Chapman
and Hall.
Fiedler, K., Walther, E., & Nickel, S. (1999). Explaining asymmetric intergroup judgment
though differential aggregation: Computer simulations and some new evidence.
European Review of Social Psychology, 10, 1-40.
Finney, H. C., & Lesieur, H. R. (1982). A contingency theory of organizational crime.
Research in the Sociology of Organizations, 1, 255-299.
Fiske, S.T. & Taylor, S.E. (2007). Social cognition. New York, NY, US: McGraw-Hill.
71
Försterling, F. (1989). Models of covariation and attribution: How do they relate to the
analogy of analysis of variance?. Journal of Personality and Social Psychology, 57(4),
615-625.
Fösterling, F. (2001). Atrribution: an introduction to theories, research and applications.
Hove, UK: Psychology Press.
Frieze, I., & Weiner, B. (1971). Cue utilization and attributional judgments for success and
failure. Journal of Personality, 39(4), 591-605.
Harris, L. T., Todorov, A., & Fiske, S. T. (2005). Attributions on the brain: Neuro-imaging
dispositional inferences, beyond theory of mind. Neuroimage, 28(4), 763-769.
Hewstone, M. & Jaspars, J. (1987). Covariation and causal attribution: A logical model of the
intuitive analysis of variance. Journal of Personality and Social Psychology, 53, 663672.
Hilton, D. J., & Slugoski, B. R. (1986). Knowledge-based causal attribution: The abnormal
conditions focus model. Psychological review, 93(1), 75-88.
Hilton, D. J., Smith, R. H., & Kim, S. H. (1995). Processes of causal explanation and
dispositional attribution. Journal of Personality and Social Psychology, 68(3), 377-387.
Hood, C. (2002). The risk game and the blame game. Government and opposition, 37(1), 1537.
Kanazawa, S. (1992). Outcome or expectancy? Antecedent of spontaneous causal attribution.
Personality and social Ssychology Bulletin, 19, 659-668.
Liden, R. C., & Mitchell, T. R. (1985). Reactions to feedback: The role of attributions.
Academy of Management Journal, 28(2), 291-308.
Lupson, J. (2007). A phenomenographic study of British civil servants' conceptions of
accountability. PhD Thesis. Cranfield University.
72
Major, B. (1980). Information acquisition and attribution processes. Journal of Personality
and Social Psychology, 39(6), 1010-1023.
Malle, B. F. (1999). How people explain behavior: A new theoretical framework. Personality
and social psychology review, 3(1), 23-48.
Mansbridge, J. (2014). A contingency theory of accountability. In M.A.P. Bovens, R.E.
Goodin & T. Schillemans (Eds.), The Oxford Handbook Public Accountability (pp. 2338). Oxford, UK: Oxford University Press.
McArthur, L.A. (1972). The how and what of why: Some determinants and consequences of
causal attribution. Journal of Personality and Social Psychology, 22, 171-193.
Mill, J.S. (1974). A system of logic ratiocinative and inductive. Toronto, Ontario, Canada:
University of Tronto Press. (Original work published 1840)
Olsen, J. P. (2013). The institutional basis of democratic accountability. West European
Politics, 36(3), 447-473.
Olsen (2014). Accountability and Ambiguity. In M.A.P. Bovens, R.E. Goodin & T.
Schillemans (Eds.), The Oxford Handbook Public Accountability (pp. 23-38). Oxford,
UK: Oxford University Press.
Orvis, B.R., Cunningham, J.D., & Kelley, H.H. (1975). A closer examination of causal
inference: The role of consensus, distinctiveness and consistency information. Journal
of Personality and Social Psychology, 32, 605-616.
Pruitt, D. J., & Insko, C. A. (1980). Extension of the Kelley attribution model: The role of
comparison-object consensus, target-object consensus, distinctiveness, and consistency.
Journal of Personality and Social Psychology, 40, 31-58.
Ruble, D. N., Feldman, N. S., & Boggiano, A. K. (1976). Social comparison between young
children in achievement situations. Developmental Psychology, 12(3), 192-197.
73
Schillemans, T. (2013). The Public Accountability Review. Working Paper. The School of
Governance, Utrecht University.
Schillemans, T., & Busuioc, M. (2015). Predicting Public Sector Accountability: From
Agency Drift to Forum Drift. Journal of Public Administration Research and Theory,
25(1), 191-215.
Sutton, R. M., & McClure, J. (2001). Covariational influences on goal-based explanation: An
integrative model. Journal of personality and social psychology, 80(2), 222- 236.
Stone, D. (2002). Policy paradox: the art of political decision making. New York, NY, US:
WW Norton.
Wong, P.T.P., & Weiner, B. (1981). When people ask “why” questions, and the heuristics of
attributional search. Journal of personality and social psychology, 40, 650-663.
Yesilkagit, K. (2009). Inspecties. In M.A.P. Bovens & T. Schillemans (Eds.), Handboek
publieke verantwoording (pp. 117-140). The Hague, The Netherlands: Lemma.
74
Appendix A: Materials
Page 1:
Met deze vragenlijst doen wij onderzoek naar beoordeling door toezichthouders op basis van
beperkte informatie. Met uw deelname helpt u onderzoek voor een afstudeerproject op het
gebied van accountability.
De vragenlijst is zeer kort; het beantwoorden van de zeven vragen kost gebruikelijk niet meer
dan enkele minuten. De verzamelde gegevens worden strikt vertrouwelijk verwerkt en zullen
niet herleidbaar openbaar gemaakt worden. Na afloop kunt u zich via een aparte pagina
registreren voor de cadeaubon en/of het rapport van dit onderzoek.
Let op! Maakt u voor navigatie alstublieft alleen gebruik van de rode knop rechtsonder de
vragen; gebruik van de back en forward knoppen van uw browser zal de enquête ontregelen.
U kunt niet terug naar een vorige pagina, uw antwoorden zijn definitief op het moment dat u
naar de volgende pagina gaat.
Page 2:
De volgende twee vragen stellen wij om zeker te zijn dat u tot de doelgroep van dit onderzoek
behoort.
Ja
Nee
Weet ik niet
Wat is de formele titel van uw huidige positie?
Page 3:
De volgende drie vragen zijn achtergrondsvragen.
Wat is uw leeftijd in jaren?
Wat is uw geslacht?
Wat is uw hoogst genoten (afgeronde) opleiding?
Basisschool
Lager voortgezet onderwijs (bijvoorbeeld VMBO, MAVO, ulo, lbo)
Voortgezet algemeen onderwijs (bijvoorbeeld HAVO, VWO, HBS)
75
Middelbaar beroepsonderwijs (bijvoorbeeld MBO, Leerlingwezen, WEB-middenkader en
specialistenopleiding)
Hoger beroepsonderwijs (HBO)
Universitair onderwijs (WO, inclusief bijv. MBA of specialisaties)
Gepromoveerd aan de universiteit
Anders, namelijk... (vul in op volgende pagina)
Page 4:
Na deze pagina volgt een zeer beperkte selectie van informatie over een fictieve organisatie.
Wij verzoeken u dit aandachtig te lezen. Hierna zullen wij u vragen naar wat volgens u
waarschijnlijk de oorzaak is van de gebeurtenis.
Page 5:
Variant 1 (actor configuration)
Een organisatie heeft een taak niet voltooid.
- Andere organisaties voltooiden deze taak wel.
- De organisatie heeft andere taken ook niet voltooid.
- De organisatie heeft dezelfde taak eerder al niet voltooid.
Variant 2 (task configuration)
Een organisatie heeft een taak niet voltooid.
- Andere organisaties voltooiden deze taak ook niet.
- De organisatie heeft andere taken wel voltooid.
- De organisatie heeft dezelfde taak eerder al niet voltooid.
Variant 3 (circumstance configuration)
Een organisatie heeft een taak niet voltooid.
- Andere organisaties voltooiden deze taak wel.
76
- De organisatie heeft andere taken wel voltooid.
- De organisatie heeft dezelfde taak eerder al wel voltooid.
Variant 4 (control configuration)
Een organisatie heeft een taak niet voltooid.
Page 6:
Op basis van de zojuist verstrekte informatie, in welke mate zijn de volgende drie zaken
volgens u waarschijnlijk een oorzaak van de beschreven situatie?
Sleep de drie 'sliders' naar de posities die het meest uw bevindingen reflecteren.
0 = geheel niet een oorzaak, 100 = geheel een oorzaak.
De organisatie
De taak
De specifieke omstandigheden
Gezien uw bevindingen, wat is er volgens u waarschijnlijk gebeurd? Geef een korte
omschrijving:
77