BLAME AVOIDANCE WITH ADJECTIVES?
MOTIVATION, OPPORTUNITY, ACTIVITY AND OUTCOME
Paper for RCPR Joint Sessions, Blame Avoidance and Blame
Management Workshop
14th-20th April 2005
Granada
Raanan Sulitzeanu-Kenan & Christopher Hood*
Introduction: two lines of analysis
This paper seeks to advance two analytic discussions in an attempt to further and integrate the
understanding of political blame-avoidance. The first is an attempt to link the current
knowledge and discussions on blame-avoidance to a common and grounded understanding of
blame. The second is to distill four conceptions of blame-avoidance that are addressed in the
current literature, and attempt to integrate them into one theoretical framework, that would be
amenable to empirical testing.1 Our title mimics that of a well-known paper by Collier and
Levitsky (1997) on ‘democracy with adjectives,’ though, as will be seen, we need to use
nouns as well.
Blame in a Political Space
The term 'blame' is defined as (to) "consider or say that somebody is responsible for
something done (badly or wrongly) or not done"; "be responsible for something bad; deserve
to be blamed"; "responsibility for something done badly or wrongly", and "criticism for doing
something wrong" (Oxford Dictionary 1989). This set of definitions points out two elements
in the notion of blame. First, that it has to do with "something bad" or "wrong". And second,
it links the "bad thing" to the responsibility of "somebody". Blame is the act of attributing a
'bad' or 'wrong' thing to a particular person or entity.
*
1
Wolfson College, Oxford; All Souls College, Oxford.
On the distinction between concept and conception, see Gallie, B. (1956) Essentially Contested
Concepts, Proceedings of the Aristotelian Society, 56: 167
2
In Felstiner et al’s (1980) well known sociological model for the emergence of legal dispute
the authors provide a sequential three stage process: naming, blaming, claiming. The first
stage begins with the notion of "injurious experience", which is defined as "any experience
that is disvalued by the person to whom it occurs" (ibid: 634). This starting point avoids more
morally loaded terms such as 'bad' and 'wrong', and sets the construction of blame on
foundations of subjective judgment. This allows a descriptive rather than normative analysis
of blame. Yet, a mere (conscious) injurious experience is not enough. "(I)n order for disputes
to emerge and remedial action to be taken, an unperceived injurious experience must be
transformed into a perceived injurious experience" (ibid: 633). This first transformation –
"saying to oneself that a particular experience has been injurious" – is called naming (ibid:
635). The next step – blaming – "occurs when a person attributes an injury to the fault of
another individual or social entity (ibid). Only when naming and blaming have occurred, can
we expect claiming to take effect – "when someone with a grievance voices it to the person or
entity believed to be responsible and asks for some remedy" (ibid: 635-6).
This conception of blame suggests that an expression of blame is the result of two elements –
a perceived negative experience, termed here perceived loss (PL), and an attribution of the
responsibility for this experience to a particular agent, termed here the agency dimension
(AD) (see: Brändström and Kuipers 2003; Bovens et al. 1999: 126; see also 'traceability' in
Arnold 1990).
The model of blame advanced here sets PL and AD in a moderation model of blame
expression, i.e. the expressions of blame (as gauged by approval ratings, retrospective voting,
protest, media criticism etc.) is the result of an interaction of PL and AD. Quite in line with
Felstiner et al. (1980), and based on a number of more recent studies in political psychology,
we maintain that since expressed blame is a directional attitude, it is not independently linked
to the size of PL, but rather is the result of an interaction between PL and the direction and
coherence of AD.
PL
Blame
AD
Figure 1: a basic model of blame
3
Blame is a directional attitude in the sense that it is measure with respect of a particular agent.
Hence for a given PL, the AD is expected to moderate the level of blame across agents. For
example, as shown in figure 2, for a given size of PL, attribution to agent D alone results in
blame for D, and no blame to any other agent. This example also models a situation of
perfectly coherent AD, i.e. attribution is solely directed at agent .
Potential Agents:
PL size
AD direction
Figure 2: PL and a perfectly coherent AD
Peffley (1985: 192) similarly argued that the effect of economic perceptions on political
evaluations is moderated by the attribution of these conditions to the target of evaluation. A
number of studies have demonstrated that responsibility attribution is a central moderator in
the relationship between perceived economic conditions and political participation
(Arceneaux 2003), and political evaluations of various agents such as the US president (Lau
and Sears 1981; Peffley and Williams 1985; Rudolph and Grant 2002; Rudolf 2003b); State
Governors (Rudolph 2003a; Stein 1990); and the US Congress (Rudolf 2003b).
Blame can vary in its degree of abstraction, in a spectrum that runs from blaming 'capitalism'
for 'the class system' to blaming particular Union Carbide managers for the 8000 avoidable
deaths of those killed at Bhopal in 1984 (Jasanoff 1994). As represented in figure 3, if, for a
given PL, relatively similar measures are attributed to many agents, AD is incoherent, and no
clear net vector of blame can be derived (represented by the dashed line around the arrows).
The impact of attribution specificity, termed here AD coherence, on the emergence of blame
had not been intensively studied. Some researchers suggest that AD coherence is inversely
4
relative to the emergence of blame. Wilson (1961) had proposed that the passive response of
black Americans to widespread problems in housing is in part a result of the large and
confusing number of culprits and potential remedies for the problems. Javeline (2003) has
found in a nationwide survey of the Russian population that "the greater the specificity of
blame attribution, the greater the probability of protest", i.e. that specificity of attribution is
linked to the expression of blame.2 Javeline has suggested that specificity may reduce the cost
of information, organization and opportunity, associated with effective public protest
(Javeline 2003: 109). Another branch of the literature lends less direct yet reasonable support
for the importance of AD coherence. A number of comparative analyses of economic voting
in Europe and in the American states report that the economy-vote/approval relationship is
attenuated in countries (or states) with divided government or high levels of coalition
complexity (Anderson 1995, 2000; Lewis-Beck 1988; Leyden and Borrelli 1995; Powell and
Whitten 1993; Rudolph 2003a).
Yet AD coherence can be addressed both at the individual level, as a personal judgment
regarding specificity of attribution (see: Javeline 2003), and at the aggregate level, as the
degree of agreement on the agent of attribution. Javeline has found that AD coherence at the
individual level is linked to the propensity to protest, yet data on the effects of AD coherence
at the aggregate level on blame expression is lacking. Further research is needed regarding the
effects of AD coherence on blame expression particularly as some BA strategies are
explained on the basis of reducing AD coherence (Weaver 1986: 'circle the wagons'; Hood
2004: 'protocolisation').
2
"… protest is an expression of anger, frustration, or moral indignation against the source of harm or
suffering" (Javeline 2003: 108).
5
Potential Agents:
Figure 3: PL and an incoherent AD
A less extreme situation is depicted in figure 3. In this case, PL is attributed to three agents,
while most of it is attributed to D, and lesser shares are attributed to C and E. This results in a
blame vector that is similar in direction to the one in figure 1, yet it can be expected to be
smaller in size (for a given PL) since it is not perfectly coherent. Some of the blame can be
directed at C and E, and/or the reduced cohesion would reduce blame expression. The level of
coherence is graphically expressed by the sharpness (or width) of the blame-vector node.
Potential Agents:
Figure 4: PL and relatively coherent AD = relatively effective blame
6
Four Conceptions of Blame-Avoidance
The existing literature on political blame-avoidance (BA) is rich and diverse, yet somewhat
sporadic its focus of interest, and lacking in common concepts. Thus our preliminary
theoretical framework for assessing the literature had begun with a basic question: ‘what
counts as blame-avoidance?’ A first reading of a substantial (though not exhaustive) sample
of the works on BA has led to a thematic division of the basic types of answers to this
question into four categories: (1) BA as motivation; (2) BA as opportunity ; (3) BA as activity;
and (4) BA as effect/consequence.
Blame-avoidance motivation
Weaver (1986) begins his well-known article by suggesting a theory of policy motivation.
This theory consists of three basic motivations: (1) credit claiming; (2) ‘good policy’; and (3)
blame avoidance. Among these three Weaver argues that most officeholders “are blame
minimizers and credit-claiming and ‘good policy’ satisficers” (1986: 372). This argument
rests on the assumption that at least some voters employ retrospective voting (Arnold 1990;
Weaver 1986: 380). Assuming that most policymakers are motivated by their desire to
maximize their prospect for re-election, Weaver notes that in translating costs and benefits
into losses and gains for officeholders the degree of concentration of the costs and benefits in
particular groups plays an important part (see also Pierson 1996). Furthermore, (given equal
concentrations of costs for losers, and benefits for gainers) studies show that losers are more
likely to notice and act on their grievance, than gainers are to act on the basis of their
improved state (Kahnemann & Tversky 1984), and this asymmetric reaction was also found in
a political context (Bloom and Price 1975; Kernell 1977; Lau 1985). Weaver thus suggests
that under such conditions “policymakers will probably attempt not to maximize credit
claiming net benefits but to minimize blame generating losses". In essence, Weaver's claim is
that under conditions of constituent loss-aversion3 (or negativity bias4), a rational
policymaker is expected to be dominantly BA motivated.5
3
The notion of ‘loss aversion’ - loss of $X is more aversive than a gain of $X is attractive (Kahnemann
& Tversky 2000: 3).
4
'Negativity bias "refers to the greater weight given to negative information relative to equally likely
positive information in a variety of information-processing tasks." (Lau 1985: 119).
5
This argument, however, ignores the possibility that a policymakers, and indeed their group of policy
advisors, would be just as much loss aversive themselves, creating an independent source for BA
7
Quantifying the 'blame-blame' zone
Based on this argument, Weaver suggests that when both net costs and benefits are high, BA
motivation can be expected to be dominant, as any losing party is more likely to respond
politically then the winning party (Weaver 1986: 378-9). Yet, how much more are people
sensitive to losses than gains? What is the size of the 'loss-aversion coefficien't? Drawing on
more recent studies of loss-aversion in risky choice (Tversky & Kahneman, 1992) and riskless
choice (Tversky & Kahneman, 1991; Kahneman, Knetsch, & Thaler, 1990) have presented
converging evidence that losses are weighted approximately two times more than equivalent
gains (the most common values for this 'coefficient of loss aversion' fall between 2 and 4)
(Heath et al. 1999). Given these measurements, we may be able to predict more specifically
the conditions that are qualitatively given in quadrant (1) of Weaver's matrix (weaver 1986:
379). Figure 4 presents the relationship between the ration of net-benefits and net-costs and
expected political response (PR) (for the formal analysis, see appendix 1).
PR
Choosing the losers
(now gainers) side
Choosing the
gainers side
‘blame-blame zone’
-0.5
-1
-2
PG/PL ratio
Figure 5: the relationship between PG/PL ratio and political response (for loss-aversion coefficient of 2)
The PG/PL ratio is the term representing the relative proportions of PG and PL. Figure 5
represents the (approximate) relationship between the PG/PL ratio, i.e. the proportion between
net benefits and net costs to the electorate, and the level of net political response, i.e. the net
valuation and resultant political response of gainers and losers. It demonstrates that when the
PG/PL ratio equals -1 (i.e. the absolute value of PG equals the absolute value of PL) net
motivation. Such a claim is based on the expectation that criticism would loom larger than equivalent
measure of praise to policymakers.
8
political response is negative, irrespective of the policy position chosen by the office-holder.
This situation exists for the range -2 < PG/PL < -o.5, and corresponds with Weaver's (1)
quadrant.6 This condition can be termed ‘blame-blame’ situation. In such a situation a
‘rational’ policy-maker is expected to employ anticipative-blame-avoidance strategies.
By using a quantified loss-aversion coefficient we can elaborate Weaver's qualitative
argument, and maintain that blame-avoidance motivation is rational for situations when net
gains are less than two-thirds and more than a third. Only if net gains exceed two-thirds is
credit claiming feasible; or when net gains falls short of one third the gainers can the officeholder gain credit by switching his position. This leaves a considerable range of cost-benefit
distributions in which BA is a rational motivation.
In real-life one can rarely quantify the PG/PL ratio. Yet this quantification provides a scale for
evaluating the need for BA activity. Furthermore, loss-aversion also implies that a reduction
of 1 unit of PL is roughly equivalent to the addition of 2 units of PG – hence a reasonable
source of BA motivation.
A second situation which gives rise to BA motivation is negative-sum game, e.g. budget cuts
(Weaver 1986: 379). "Retrenchment is generally an exercise in blame avoidance rather than
credit claiming, primarily because the costs of retrenchment are concentrated (and often
immediate), while the benefits are not" (Pierson 1996: 145). Advocates of such policies
confront a clash between their policy preferences and their electoral considerations. A similar
situation is when personal or policy interests of the policymaker and constituents are opposed,
e.g. congressional pay rises (Weaver 1986: 380).7
Where Adjectives Come In: Anticipatory and Reactive Blame-Avoidance
Kathleen McGrew (1991) has commented on Weaver's (1986) work that 'avoidance of a
blame generating situation is not always possible', and politicians may find themselves in a
situation for which they will be blamed. McGrew refers to these 'after-the-fact damage control
6
This range is between -2 < PG/PL < -1 if we consider only the possibility of siding with the gainers
group. Yet is switching sides is an option, represented by the left side of the graph ('jump on the
bandwagon', Weaver 1986), then the upper limit of the range is -0.5.
7
The third situation given by Weaver refers to ‘consensus violation’ situations (p. 380). Such a
situation is the only case of reactive blame-avoidance in his list, and doesn’t appear to play a central
role in his discussion (note the absence of this situation in Table 3 in p. 385).
9
tactics as blame management strategies' (1991: 1135). Similarly, in Hart’s review of Richard
Ellis’ Presidential Lightning Rods (1994), he notes the failure to clearly distinguish between
keeping out of trouble and deflecting blame for trouble not avoided (1995: 1022). Arnold
(1990) explicitly makes this distinction while noting that US Congress members may
recognize the potential criticism certain policies can bring about. Such policies are voted
against whether or not concrete opposition exists, “in anticipation of future punishment, not
in response to current pressures" (1990: 75). It appears that we should distinguish between
two distinct phases of blame avoidance activity.
In the first, the political act occurs prior to the emergence of blame, or the occurrence of a
blame-generating event, as an anticipatory act. In the second, the political act comes after the
emergence of blame, as a reactive act. The two phases of blame avoidance activity differ in
their temporal arrangement with respect to the emergence of blame. We seek to employ this
distinction in the analysis, and use the term 'anticipatory blame avoidance' (ABA) for the
political strategies which are employed prior to the generation of blame, and the term 'reactive
blame avoidance' (RBA) to denote the strategies employed after the introduction of blame.8
The political motivation for reactive blame avoidance lies in the dangers of 'politicized
failures'. Such events provide critics of policy makers with a signal that 'something is rotten'
(Kingdon 1995: 98; Brändström and Kuipers 2003: 281). Studies of how such situations lead
to blame games include Ellis (1994), Bovens and 't Hart (1996), Bovens et al. (1999), and
Brändström and Kuipers 2003).
Blame-avoidance opportunity
'As every reader of detective stories knows, motive is one thing and opportunity is another.
For blame avoidance, opportunity consists of the extent to which it is possible for players by
strategic behaviour to mitigate or avoid blame. The notion of blame-avoidance opportunity
refers to the set of given conditions (rather than actions) that provide varying degrees of
protection from public blame. These conditions may include institutional characteristics, party
system constellation and the arrangement and comprehensiveness of social cleavages. This
conception of blame-avoidance is probably the least studied so far.
8
This adjectival terminology is preferred to that of McGraw because it allows the usage of the term
'blame-avoidance' generically, and add the prefixes (anticipatory / reactive) when it is relevant.
10
However, the literature, such as it is, suggests several factors that may shape BA opportunity.
The first is by providing conditions which impede the construction of blame. It relates to the
relationship between institutional structure and the element of agency-dimension. As noted
above, a number of comparative analyses of economic voting in Europe and in the American
states have found that the relationship between economic perceptions and vote/approval
attitudes is attenuated in countries (or states) with divided government or high levels of
coalition complexity (Anderson 1995, 2000; Lewis-Beck 1988; Leyden and Borrelli 1995;
Power and Whitten 1993; Rudolph 2003a). In other words, when people are faced with a
complicated institutional structure of government, or when decision making appears to be the
product of a large and diverse group, AD coherence appears to diminish, and consequently so
does blame expression, even while PL remains intact (as inferred from the findings above).
The second way BA opportunity influences the politics of blame is by providing conditions in
which blame is not channeled into political activity. This dynamic is unique in the sense that
it does not appear to affect the elements of blame, but rather constituents' 'calculus of
deterrence'. The voice and exit options available for constituents, determines the degree by
which they can act upon their grievances (Hirschman 1970). Furthermore, the absence of a
feasible exit can be also expected to impede voice (ibid). This is basically a matter of political
choice. Anderson (1995) has found that the popularity of right wing parties is relatively less
vulnerable to criticism regarding the level of inflation, and Ross (2000) suggests that left wing
parties receive relatively less public criticism for welfare retrenchment decisions. Another
example is a common (yet untested) observation regarding Israeli politics which states that
only a hawkish government (a Likud led coalition) can make territorial concessions in the
Israeli-Palestinian peace process, and maintain adequate public support. These examples
suggest that a particular constellation of party competition (Kitschelt 2001) may provide BA
opportunity for particular unpopular policies, by affecting the availability of political options
in response to these policies.
The third type (and least empirically studied) of BA opportunity relates to the conditions
which facilitate or encumber the effectiveness of BA activity. This aspect of BA opportunity
requires greater understanding and knowledge about BA activity and particularly BA outcome
(discussion below). For example, Horn's (1995) criticism of Fiorina's (1982) "shift the
responsibility" rationale for delegation (elaborated upon below). Horn’s criticism consists of
two points. First, as Fiorina concedes, the model is limited by the degree of concentration of
interests. However, even in diffused interest Horn maintains that “the best strategy of the
rationally ignorant may well be to judge their representatives on the basis of outcomes and not
try to apportion blame” (1995: 45). Horn supports this hypothetical possibility by the claim
11
that the doctrine of ministerial responsibility in the Westminster system means just that.
Therefore, "if diffused interests act this way [should say 'may act'] then the main reason
advanced for 'shifting responsibility' carries no weight" (ibid). Horn's second point is that the
"shift the responsibility" model works only when lines of responsibility are unclear. Since
delegation to semi-independent regulatory agencies are common in parliamentary systems
too, which have clear lines of responsibility, Horn concludes that in "countries with a
parliamentary system, legislators cannot shift the responsibility for administrative decisions,
yet they still delegate authority to relatively independent administrators" (1995: 46).
In the first point Horn begins by suggesting that a strategy which “may” be employed is to
judge representative on the basis of outcomes, and continues to claim that such a strategy is
embodied in the doctrine of ministerial responsibility in the Westminster system. His basis for
the first claim relies on a normative convention – the doctrine of ministerial responsibility in
Westminster systems – rather than on empirical finding. The second point is even more
general, i.e. that parliamentary systems have clear lines of responsibility. This sweeping claim
is again drawn from a legal article (Bishop 1990: 499), yet it is not backed by empirical
evidence.9 To conclude, Horn’s rejection of Fiorina’s SR model should not be taken as
conclusive.
It is interesting to note that although in this debate over the ability of legislators to shift
blame, the argument was that a parliamentary system is less amiable than a presidential
system, an opposite claim has been made with respect to the ability of the head of the
executive to shift blame. Harold Laski in ‘The American Presidency’ (1940) argued that an
American president cannot deflect blame onto subordinates, due to his personal position as
head of the executive branch, while in the British case, blame is directed at an anonymous
entity - 'the government' (Ellis, 1994: 2; Hood 2002, 2004).
Blame-avoidance activity
The starting point for our discussion of BA activity consists of the works of Weaver (1986,
1988), Arnold (1990) and Hood (2002), which we attempt to integrate them with the broader
theoretical framework of this paper. BA activity can be categorized on the basis of the
9
A distinction her is drawn between the effects of institutional structure on the emergence of balme
(type 1 BA opportunity) for which empirical evidence exists (as note above), and the relations between
institutional structure and the effectiveness of BA activity, such as delegative strategies (Hood 2002),
for which empirical evidence is lacking.
12
concept of blame. Thus BA activity can be shown to operate by targeting loss, perceived-loss,
agency-dimension, or blame expression.
One of us (Hood 2002) has suggested three broad ways that are available to politicians
seeking to avoid or mitigate public blame: (1) presentational strategies ('impression
management', Schlenker 1980); (2) policy strategies (Twight, 1991); (3) agency (or
delegation) strategies. The article from which that trichotomy is taken concentrates on the
third approach (ibid: 16-7).
Presentational strategies are “attempts to avoid or limit blame by spin, timing, stagemanagement and argument, for example by offering plausible excuses, turning blame into
credit or diverting public attention onto other matters". Presentational strategies further divide
into argumentative strategies (excuses and justifications) and non-argumentative ones
(Loquocentric - lies: about facts, and non-loquocentric - non-engagement, diversions, covert
attempts to fix public agenda). Non-argumentative strategies may be used more frequently
when trust in the blamee falls to a low ebb (Hood 2004).
Agency strategies are "attempts by officeholders or institutions to avoid or limit blame by the
way that formal responsibility, competency or jurisdiction is allocated among institutions and
officeholders" (Hood 2004, 2002: 16). This category includes delegative and directive
strategies. Directive strategies divide into temporary and permanent ones. Delegative
strategies divide into hard (legal/constitutional) and soft (revocable, managerial) delegation
(Hood 2004). This categorization does not exclusively subscribe to the typical argument that
uses BA motivation as a possible explanation of delegation (Fiorina 1982), suggesting the
alternative to delegation - termed 'directive strategies', or taking charge – as another way to
mitigate blame.
Policy strategies are "attempts by officeholders or institutions to avoid or limit blame by the
substance or content of what they do rather than in how its presentation is handled or who is
placed in the front line of responsibility for directing it". These strategies are divided into
aggregative policies - directed towards group interests, and defensive policies - aimed at
limiting officeholders' liability or blame. Aggregative policies may be pro risk-producer, or
pro risk-victim (Twight 1991). Defensive strategies may take the form of protocolization and
other non-discretionary processes, or abandonment and closure of potentially blame
generating services (Hood 2004).
13
BA activity aimed at PL
An obvious (yet not necessarily practical) way of avoiding blame for unpopular consequences
of a certain policy is to avoid the policy altogether or alter its content. Arnold (1990) notes
that fear of retrospective voting leads legislators to avoid a class of policy alternatives he calls
politically infeasible policies. Those are policies that “would impose large and direct early-order costs”
on constituents (1990: 74-5). This example is an extreme case of 'aggregate policy strategies'
(Hood 2004). A more moderate version of such strategies is part of the 'new politics' of
welfare retrenchment, as policy-makers try to play off one group of beneficiaries against
another and develop reforms that compensate crucial groups for lost benefits (Pierson 1996).
Another example of such a strategy is 'Throw Good Money after Bad' Weaver (1986), i.e.
attempts to delay adverse outcomes by committing extra resources to shore up the status quo.
As we turn to perceptions, the available repertoire of BA strategies expands. Argumentative
strategies can be used, more specifically justifications, as they deny some or any measure of
offensiveness in act for which the individual admits responsibility" (Semin and Manstead
1983: 800, in McGraw 1991: 1136). Justifications express attempts to reframe the undesirable
outcome so that it is viewed as more favorable (ibid: 1137).
Edelman (1977, 1988) works on political language and political symbols, provide rich
background on such strategies. He (1977) discusses a number of classic bureaucratic
justifications of governmental policies that recur in response to criticism, such as: (1) the
action that arouses anxiety is 'routine'; (2) the harm caused is helpful, and in the end the
victims will be better off; (3) it is necessary to destroy in order to save - "you cannot make an
omelet without breaking some eggs"; (4) make grandiose claims about the positive effects of
the program; or (5) reframing - by adopting a different perspective, the policy has been an
overall success - introduction of different criteria for success and failure (Bovens et al. 1999).
Another way to influence perceived loss is simply secrecy. Secrecy regarding the policy and
its implications may limit or at least delay the emergence of perceived loss. Where secrecy is
not tenable diversions are a further option. In the legislative context one method is “to
combine various proposals into a single omnibus bill so that legislators vote on an entire
package rather than on each of the individual pieces” (Arnold 1990). The essence of this
strategy is to hide a decision in a multitude of other decisions. In a way it is on the other end
of the range from secrecy – hiding a message by ‘over-information’, rather than ‘underinformation’.
14
BA activity aimed at Agency dimension
As noted above, the agency dimension refers to the attribution of responsibility for the
perceived loss to a particular agent. Arnold (1990) uses the term traceability for the degree to
which citizens can trace an observed effect to a governmental action and back to a
representative’s individual contribution. Traceability requires three conditions: (1) a
perceptible effect; (2) an identifiable governmental action; and (3) a legislator’s visible
contribution (1990: 47-8). Traceability is dependent on what is perceived as the causal logic
between its three conditions (ibid: 48-9), and therefore it is not only the acts of politicians
which affect retrospective voting, but more importantly the ways in which these acts are seen
or hidden by the electorate that matter. “Weakening the traceability chain is a superb method
for protecting legislators from their constituents’ wrath for imposing costs on them” (ibid:
100-1).
In the model of blame advanced in this paper, agency dimension is defined by two properties:
its direction, determined by the target of attribution, and its coherence, determined by the
selectiveness and consistency of attribution. Both of these properties are targeted by various
types of BA activity.
Argumentative strategies address AD direction as well as cohesion. Specifically excuses, as
they deny some or any measure of responsibility for what is admittedly an offensive act, i.e.
without denying the loss. Excuses involve an attempt to weaken the perceptions of the causal
link between the actor and an undesirable outcome (McGraw 1991: 1137), effectively
removing the direction of blame from his/her direction (see figures 4 above). Other excuses
include horizontal diffusion of responsibility, such as Thompson's (1980) 'many hands' claim,
and vertical diffusion of responsibility. Both can be used to affect AD coherence ('many
hands') and/or AD direction (referring to operational error etc.).
A more subtle strategy to influence agency dimension is by delegation. One of us has
identified three blame shift strategies of this type: privatization (with respect to financial
failures), managerialization (for organizational malfunctioning), and expertization (in cases of
judgmental failures). Each of these moves provides a relevant alternative target of blame
(private companies, managers, and experts, respectively). These, and other such strategies that
do not delegate to law courts or to other elected levels of government, allow politicians to
play the 'blame game', but at the same time direct policy by behind the scenes intervention
(un-acknowledgeable means). However, it is expected that such strategies would lose
credibility over the long run, leading to blame-reversion (Hood, 2002: 28).
15
A further possible factor affecting the effectiveness of delegation as a BA measure is the
‘credibility of delegation’ (Hood 2002: 25). This issue relates to the distinction between
anticipatory and reactive BA. The credibility of delegation can be maintained, and hence its
effectiveness as a BA strategy, when it is used as an anticipatory BA. Once blame has
surfaced, ex-post delegation is not expected be an effective in shifting blame.
Secrecy can also be used to address the issue of agency dimension. When proceedings are
conducted in camera, or when votes are unrecorded, even if the outcome is known, can
provide some shelter as the contribution of each participant is not known (Arnold 1990: 102;
see also: 'circle the wagons' in Weaver 1986).
Other strategies, such as protocolization (Hood 2004) or indexation (Weaver 1986, 1988) also
act to reduce AD coherence. They provide a formal, yet typically ambiguous narrative as to
the locus of discretion in the relevant decision.
BA activity aimed at blame salience
The final chain in the emergence of blame is simply its expression. For the purpose of this
paper this means the projection of the attitude of blame, as a specific directional attitude, into
human behaviour, such as protest, political participation, political violence, media criticism
and elite criticism. A further type of blame expression is its translation into general political
evaluations. In all these transformations, the specific blame attitude enters a competition over
attention with other issues and considerations. It is possible that a citizen or a journalist will
blame the minister of agriculture for her position on GM crops. Yet will such an attitude
cause the citizen to change his vote in the next elections, or his overall approval rate for the
government? Will it bring the journalist to convey this attitude in an article, and will pass the
editorial screening and indeed be published?
The factor that plays a major role in determining the actual effect of blame attitude on blame
expression is (relative) salience. For example, widespread blame of Tony Blair's government
for the Millennium dome fiasco in Britain in 2000 did not seriously threaten Blair's reelection prospects in 2001 because the Dome was not salient relative to other electoral issues
such as public services and the economy (see Jennings 2004). Hence blame expression (BE)
towards a particular agent is a function of the salience (S) of PL, for a given AD:
BE = ao + S * PL * AD + u
16
where ao represents the intercept and u is a disturbance term that captures other sources of
blame expression.10
Salience is influenced, inter-alia, by media agenda setting (Behr and Iyengar 1985), and so an
important element in this process is the public agenda. It should be noted that public agenda
can include blame expression, i.e. media and elite criticism, as well being as a factor
determining (future) blame expression (since it affects salience).
Public agenda is susceptible to influences, and therefore, can be a target of BA activity. Such
activities include non-argumentative strategies (Hood 2004) such as non-engagement,
diversions, covert attempts to fix public agenda, directive strategies, i.e. 'concede-and-moveon', or possibly, of the appointing of official investigations (Bovens et al. 1999; Brändström
and Kuipers 2003). These strategies are employed when blame was not successfully avoided
by targeting its preceding elements. They are not aimed at changing the particular blame
attitude, but rather to limit its influence on behaviour.
PL
Blame
AD
BA efforts to minimize PL
Aggregate policy strategies
Presentational strategies
BA efforts to conceal / shift / obscure AD:
Conceal: institutional secrecy (Arnold, Bovens et al 1999, Shapiro
1998); Protocolization (Hood 2003), ‘Automatic government’
(Weaver 1988); Shift: Delegative strategies (Hood 2002); Pass the
buck (Weaver 1986); Shift blame (Fiorina 1981); Lightning rods
(Ellis1994); Presentational strategies (Hood 2002); Obscure: Circle
the Wagons (Weaver 1986); ‘Many hands’ (Thompson1980)
BA efforts to limit blame salience
Non-argumentatuve, directive (Hood
2004), official investigations
(Bovens et al 1999; Brändström and
Kuipers 20030
Figure 6: categories of BA activity
10
This model explicitly distinguishes between 'salience' as a measure of importance, and PL, as a
measure of the perceived negativity of the situation. This distinction conforms with Wlezien's work,
which criticises the typical measure of salience as "most important problem".
17
Blame-avoidance outcome
When shifting the focus of analysis from strategies to their expected effects, a clear
distinction can be drawn between strategies that attempt to directly affect the public's blame
attribution judgments, and strategies that endeavor to influence public agenda. This
distinction is similar to the difference between influencing 'what people think' (responsibility
judgment), and 'what people think about' (Entman 1989). The former has to do with 'opinion
shaping', while the later with agenda control. This distinction is particularly relevant from a
methodological aspect, when one attempts to empirically study these effects. Agenda effects
can be measured by media coverage, parliamentary motions and discussions, and legislative
proposals while blame judgments can be gauged through public opinion questionnaires and
interviews.
The reliance on a concept of blame facilitates greater detail in designing and measuring BA
outcome. Addressing measures of PL, AD, and blame-expressions separately (one good
example of this is Javeline 2003), can further the understanding of more nuanced effects of
various BA strategies. Although it may be that the ultimate test for the effectiveness of a BA
strategy is the level of blame expression or its translation into political support
(vote/approval), it is important to understand whether this outcome is the result of affecting
PL or AD, as each case has secondary implications. For example, if AD is involved, one
should seek to find which other agent was 'sacrificed', i.e. was attributed greater
responsibility, for attaining the BA outcome for the agent in question.
Discussion
Can these different adjectival conceptions of blame-avoidance help to focus the rather diffuse
notion of blame-avoidance? What are the necessary conditions that must be met before we
can sensibly define an activity as BA? Is it the motivation that prompted the activity, the
consequences of the activity, or both? That question takes us into classic issues of
intentionality (as in the literature on political power). For instance, does it make sense to
classify activity as 'blame avoidance' if it stems from 'good policy' motivation (meaning that
we end up classifying Mother Teresa or other altruistic ascetics as ‘blame avoiders’)?11 And
11
One examples of this latter category is Weaver's (1986) ‘stop-me-before-I-kill-again’ strategy. The
question of motivation may divide between first-order BA - activity that is aimed at shifting or reducing
blame towards the officeholder – and second-order BA –activity which is aimed at increasing the
prospect of ‘good policy’ by avoiding potentially blame-generating situations. In this sense, it would be
wrong to categorize the creation of independent banks under first order BA, as this delegates both
18
contrariwise, does it make sense to classify behaviour as blame avoidance even if it is not
effective (with little or no BA outcome)?
We would argue that is it important not to run together BA outcome and BA activity. By
keeping those two things separate, we can explore both successful and unsuccessful BA
activities, following the notion of unintended consequences of human action that is central to
the social sciences. However, we would also argue that an important condition for classifying
activity as BA activity is motivation. Absent motivation, we are left with no clear reason to
call a political activity 'blame avoidance' – particularly when unsuccessful. The main problem
with motivation is empirical. It is of course difficult to provide direct evidence for BA
motivation, but such evidence can be found sometimes and methodological difficulty should
not dictate theory development. Motivation can sometimes be indirectly inferred, e.g. by
covariations of blame expression and a particular activity, though this option is limited to
reactive BA.
The study of political blame avoidance is somewhat lacking in empirical research, most
particularly regarding BA outcome. Integrating the four conceptions of blame avoidance and
linking them to an overall model of blame, may facilitate hypotheses formation and testing.
As can be seen in figure 6, the construction of blame relies on some perceived loss, which
together with the properties of agency dimension yields blame. Hence, any successful
mitigation along the sequence, is expected to carry on to the next stages linked to it. For
example, a reduction in actual loss can be expected to result in a diminution in perceived loss;
a mitigation of PL would reduce the level of expressed blame; and a change in the direction
and possibly coherence of AD would result in a change in the blame directed at particular
agents. Yet this also means that a successful mitigation in PL is not necessarily linked with a
reduction in actual loss, and a decrease in blame expression is not necessarily linked with a
change in PL or AD.
Though we have titled this paper ‘blame avoidance with adjectives’ and we think it is
important to distinguish between anticipatory and reactive blame avoidance, successful and
unsuccessful blame avoidance, we cannot do without nouns as well as adjectives (or at least
we have to turn BA into an adjective attached to other nouns). And the four blame avoidance
elements suggested by this framework are assumed to maintain particular relationships, as
depicted in figure 7. BA opportunity is expected (by definition) to influence BA motivation,
blame and credit, and it reasonably plausible that the motivation is good-policy, but the inherent
limitations of political life require a second-order BA strategy.
19
either by providing conditions which impede the construction of blame, channel blame away
from political activity; and BA activity and outcome by influencing the effectiveness of
particular BA activity. The two-way arrow between BA opportunity and activity represents
the possibility that BA activity may influence the range of BA opportunity over time (Hood
2004).
BA motivation is expected to relate to BA activity. Further research is needed to study more
particular relationships between anticipatory and reactive motivations and officeholders'
selection among BA strategies. BA activity targets the three elements of blame expression,
which jointly produce BA outcomes – expressed either by opinion shifts and/or agenda
control. The two-way arrow between salience and BA outcome represents the expectation that
salience determines BA expression, which feeds back into salience.12
BA
opportunity
BA
motivation
BA
activity
Anticipatory
Reactive
PL
AD
Salience
BA
outcome
Opinion shaping
Agenda control
Figure 7: Adjectives of blame avoidance
This theoretical framework is empirically oriented, in the sense that the analytic discussion is
intended to lend itself to historical and empirical testing and refinement of the relationships it
depicts. And the time is ripe for such a framework, because recent developments in research
methods, polling and paneling techniques, as well as statistical and technological
12
Thus this model is expected to be non-linear and possibly a threshold model, see: Wood 2003
20
developments such as internet polling, provide new ways of testing the various relationships
between the four elements of blame avoidance, and their relationships with the elements of
blame. Additional findings are needed to test, correct and refine this theoretical framework.
21
Appendix 1: Formal analysis of the loss-aversion influence on net
political response
r – utility at the reference point (status-quo)
PU – perceived utility (A perceived gain (PG) is defined by: PU > r ; a perceived loss (PL) is
defined by PU < r)
PR – political response
AD – agency dimension (agent identified as cause/responsible for the value)
PR = f (PU)
{for PU > r} = b1 * PU {b1 > 0}
{for PU < r} = b2 * PU {b2 > 0}
Loss-aversion coefficient = b2/ b1
2; b = b1 = .5 b2
Thus:
PR =
{for PU > r} b * (PU - r)
{for PU < r} 2b * (PU - r)
[a negative value]
In a two party (group) competitive game:
Net-PR = PR1+PR2 = b * (PU1 - r) + 2b * (PU2 - r)
/PU2
If: Net-V = 0:
b * (PU1 - r) = -2b * (PU2 - r)
(PU1 - r) = -2(PU2 - r)
If: Net-V = 0 when the absolute value of the gain is twice the absolute value of the loss (for
LA-coefficient of 2)
If (PU1 - r) = -(PU2 - r), then:
Net-V = -b * (PU2 - r) + 2b * (PU2 - r) = b * (PU2 - r), i.e. a negative value that equals the
loss * b
22
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