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Cited by 268

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Nonconsequentialist decisions

Baron, Jonathan·1994·Behavioral and Brain Sciences

Abstract

According to a simple form of consequentialism, we should base decisions on our judgments about their consequences for achieving our goals. Our goals give us reason to endorse consequentialism as a standard of decision making. Alternative standards invariably lead to consequences that are less good in this sense. Yet some people knowingly follow decision rules that violate consequentialism. For example, they prefer harmful omissions to less harmful acts, they favor the status quo over alternatives they would otherwise judge to be belter, they provide third-party compensation on the basis of the cause of an injury rather than the benefit from the compensation, they ignore deterrent effects in decisions about punishment, and they resist coercive reforms they judge to be beneficial. I suggest that nonconsequentialist principles arise from overgeneralizing rules that are consistent with consequentialism in a limited set of cases. Commitment to such rules is detached from their original purposes. The existence of such nonconsequentialist decision biases has implications for philosophical and experimental methodology, the relation between psychology and public policy, and education.

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Metadata

Authors
Baron, J.
Venue
Behavioral and Brain Sciences
Published
1994-03
Volume
17
Issue
1
Pages
1-10
ISSN
  • 0140-525X (ISSN-L)
  • 1469-1825
OpenAlex
W4211198509
Cited by
268
References
16
FWCI
5.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nonconsequentialist decisions. https://app.cochat.ai/papers/10.1017/s0140525x0003301x
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Baron, J. (1994). Nonconsequentialist decisions. Behavioral and Brain Sciences. https://doi.org/10.1017/s0140525x0003301x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.