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Record W3005353123 · doi:10.1177/1745691619885840

The Moral Psychology of Raceless, Genderless Strangers

2020· article· en· W3005353123 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerspectives on Psychological Science · 2020
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsMcGill University
FundersKoch FoundationRussell Sage FoundationNational Science Foundation
KeywordsPsychologySocial psychologyMoral psychologySocial cognitive theory of moralityMoralityMoral disengagementHarmSocial identity theoryIdentity (music)Moral reasoningCausationSocial cognitionMoral developmentSuspectSocial intuitionismCognitionSocial groupEpistemologyCriminology

Abstract

fetched live from OpenAlex

Moral psychology uses tightly controlled scenarios in which the identities of the characters are either unspecified or vague. Studies with raceless, genderless strangers help to highlight the important structural elements of moral acts (e.g., intention, causation, harm) but may not generalize to real-world judgments. As researchers have long shown, social judgments hinge on the identities (e.g., race, gender, age, religion, group affiliation) of both target and perceiver. Asking whether people generally condemn "shooting someone" is very different from asking whether liberals as opposed to conservatives condemn "a White police officer shooting a Black suspect." We argue for the importance of incorporating identity into moral psychology. We briefly outline the central role of identity in social judgments before reviewing current theories in moral psychology. We then advocate an expanded person-centered morality-synthesizing moral psychology with social cognition-to better capture everyday moral judgments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.246
GPT teacher head0.394
Teacher spread0.148 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it