Evidence map›Paper›PMID 33561377›Full record

ReviewJournal of the Royal Society, Interface2021

Mathematical foundations of moral preferences.

Valerio Capraro, Matjaž Perc

Abstract readReview
In one paragraph

Review in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

66 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Language-based game theory in the age of artificial intelligence.Journal of the Royal Society, Interface · 2024
    Pooled it
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  6. Counterfeit judgments in large language models.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Why people follow rules.Nature human behaviour · 2025
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  13. Social learning with complex contagion.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Valerio CapraroDepartment of Economics, Middlesex University, The Burroughs, London NW4 4BT, UK.
Matjaž PercFaculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary pay-offs of others. However, during the last 10 years, research has shown that different types of unselfish behaviour, including cooperation, altruism, truth-telling, altruistic punishment and trustworthiness are in fact better explained by preferences for following one's own personal norms-internal standards about what is right or wrong in a given situation. Beyond better organizing various forms of unselfish behaviour, this moral preference hypothesis has recently also been used to increase charitable donations, simply by means of interventions that make the morality of an action salient. Here we review experimental and theoretical work dedicated to this rapidly growing field of research, and in doing so we outline mathematical foundations for moral preferences that can be used in future models to better understand selfless human actions and to adjust policies accordingly. These foundations can also be used by artificial intelligence to better navigate the complex landscape of human morality.

Indexed as

AltruismArtificial IntelligenceCooperative BehaviorHumansMathematicsMoralsPunishmentaltruismcooperationhonestymathematical modellingmoralityutility function

Identifiers

PMID33561377
PMCPMC8086879

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.