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Record W4327682232 · doi:10.1007/s10508-023-02571-0

Worth the Risk? Greater Acceptance of Instrumental Harm Befalling Men than Women

2023· article· en· W4327682232 on OpenAlexaff
Maja Graso, Tania Reynolds, Karl Aquino

Bibliographic record

VenueArchives of Sexual Behavior · 2023
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHarmPsychological interventionPsychologyIntervention (counseling)Social psychologyDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Scientific and organizational interventions often involve trade-offs whereby they benefit some but entail costs to others (i.e., instrumental harm; IH). We hypothesized that the gender of the persons incurring those costs would influence intervention endorsement, such that people would more readily support interventions inflicting IH onto men than onto women. We also hypothesized that women would exhibit greater asymmetries in their acceptance of IH to men versus women. Three experimental studies (two pre-registered) tested these hypotheses. Studies 1 and 2 granted support for these predictions using a variety of interventions and contexts. Study 3 tested a possible boundary condition of these asymmetries using contexts in which women have traditionally been expected to sacrifice more than men: caring for infants, children, the elderly, and the ill. Even in these traditionally female contexts, participants still more readily accepted IH to men than women. Findings indicate people (especially women) are less willing to accept instrumental harm befalling women (vs. men). We discuss the theoretical and practical implications and limitations of our findings.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.093
GPT teacher head0.299
Teacher spread0.206 · 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 teacher head, 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

Citations11
Published2023
Admission routes1
Has abstractyes

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