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Record W4205675975 · doi:10.31234/osf.io/9y3wp

Navigating between punishment, avoidance, and instruction: The form and function of responses to moral violations varies across adult and child transgressors

2021· preprint· en· W4205675975 on OpenAlexafffund
Cindel White, Mark Schaller, Elizabeth G. Abraham, Joshua Rottman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British ColumbiaYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial psychologyDistancingPunishment (psychology)Interpersonal communicationDevelopmental psychologyAnxietySocial distancePersonality psychologyInterpersonal relationshipAltruism (biology)PersonalityCoronavirus disease 2019 (COVID-19)Medicine

Abstract

fetched live from OpenAlex

Immoral actions can elicit a wide array of responses, ranging from pugnacious confrontation to passive distancing. What leads onlookers to react so differently to various violations? Across four studies (N = 2,085), we investigated how responses vary depending on whether moral transgressions are committed by adults or by children. Findings reliably demonstrated that adult participants were more likely to avoid adult transgressors, and more likely to instruct child transgressors about why their actions were wrong. These patterns arose from varying cost-benefit structures, derived in part from asymmetries in interpersonal power between adults and children, rendering adults’ direct confrontation of children both less costly and more beneficial. Although adults’ transgressions were judged to be relatively more wrong, participants had greater anxiety about the negative consequences of confronting adults, and they viewed adults’ personalities as less malleable, thus diminishing the effectiveness of confrontation. In contrast, 4- to 9-year-old children did not differ in their willingness to avoid or instruct adult and child transgressors. Across studies, the content of transgressions (e.g., being harmful or impure) mattered little for determining the nature of responses. Overall, diverse responses to moral transgressions were uniquely tailored to the different costs and benefits associated with confronting adult and child transgressors.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.322
Teacher spread0.245 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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