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Record W2162631703 · doi:10.1177/0956797610384150

Why Women Apologize More Than Men

2010· article· en· W2162631703 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePsychological Science · 2010
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychology

Abstract

fetched live from OpenAlex

Despite wide acceptance of the stereotype that women apologize more readily than men, there is little systematic evidence to support this stereotype or its supposed bases (e.g., men's fragile egos). We designed two studies to examine whether gender differences in apology behavior exist and, if so, why. In Study 1, participants reported in daily diaries all offenses they committed or experienced and whether an apology had been offered. Women reported offering more apologies than men, but they also reported committing more offenses. There was no gender difference in the proportion of offenses that prompted apologies. This finding suggests that men apologize less frequently than women because they have a higher threshold for what constitutes offensive behavior. In Study 2, we tested this threshold hypothesis by asking participants to evaluate both imaginary and recalled offenses. As predicted, men rated the offenses as less severe than women did. These different ratings of severity predicted both judgments of whether an apology was deserved and actual apology behavior.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.027
GPT teacher head0.382
Teacher spread0.355 · 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