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. 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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). 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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