Culpable Control and Counterfactual Reasoning in the Psychology of Blame

Abstract

Many counterfactual reasoning studies assess how people ascribe blame for harmful actions. By itself, the knowledge that a harmful outcome could easily have been avoided does not predict blame. In three studies, the authors showed that an outcome's mutability influences blame and related judgments when it is coupled with a basis for negative evaluations. Study 1 showed that mutability influenced blame and compensation judgments when a physician was negligent but not when the physician took reasonable precautions to prevent harm. Study 2 showed that this finding was attenuated when the victim contributed to his own demise. In Study 3, whether an actor just missed arriving on time to see his dying mother or had no chance to see her influenced his blameworthiness when his reason for being late provided a basis for negative evaluations but made no difference when there was a positive reason for the delay. These findings clarify the conditions under which an outcome's mutability is likely to influence blame and related attributions.

Variations in judgments of intentional action and moral evaluation across eight cultures

“…On the other hand, if the information about the actors or consequences is positive enough, it may even override contradictory evidence (e.g., a thriving economy or environment may be enough to deemphasize the cavalier attitude of the protagonist). Culture may influence judgments of intentional action not only by defining what acts are considered helpful versus harmful, but also perhaps by setting the threshold for how negative outcomes or agents must be before they are considered blameworthy (Alicke et al, 2008). Our findings may also call to question the assumption that transculturally, punitive measures carry higher instrumental value than reward (Henrich et al, 2006).…”

“…If the relationship between moral evaluation and judgments of intentional action can be multi-directional, as our findings suggest, how can we predict what circumstances will increase or decrease blame attributions? Alicke, Davis, Buckingham, and Zell (2008) point to a ''culpable control" model in which participants evaluate causal information alongside the favorability of the outcome or actors. Assignations of blame may be made when an agent is perceived as controlling a negative outcome (as in the harm condition), but also if evidential information suggests that an actor is dislikeable or is shown to be negligent (as might be the perception following the protagonist's casual disregard for the environment).…”

Causal superseding

“…For example, a series of studies have found that people"s judgments are often distorted by "blame validation" (Alicke, 1992;Alicke, Buckingham, Zell, & Davis, 2008; RUNNING HEAD: CAUSAL SUPERSEDING 6 Lagnado & Channon, 2008), a motivational bias to assign causality to people who are blameworthy, with only minimal regard for their actual causal status. Subsequent work has extended this account to include "excuse validation" (Turri, 2013), the motivation to not assign causality to individuals whom we do not feel are blameworthy.…”

Political differences in free will belief are driven by differences in moralization

“…For example, research has repeatedly shown a praise-blame asymmetry in judgments of intentional action: people are more inclined to say that a behavior with negative side-effects was performed intentionally than an identical action with positive side-effects (Knobe, 2003;Pettit & Knobe, 2009). Motivated judgments of others' behavior are most pronounced in -and perhaps even driven by -cases in which the behavior is seen as harmful (Alicke, Buckingham, Zell, & Davis, 2008). All else being equal, the desire to blame another for bad behavior is more potent than the desire to praise another for their good behavior (Clark, Schniderman, Baumeister, Luguri, & Ditto, 2017).…”