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Record W1978000811 · doi:10.1177/0146167206286709

Sex Differences in Regret: All For Love or Some For Lust?

2006· article· en· W1978000811 on OpenAlexaff
Neal J. Roese, Ginger L. Pennington, Jill M. Coleman, Maria Janicki, Norman P. Li, Douglas T. Kenrick

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2006
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsSimon Fraser University
FundersNational Institute of Mental Health
KeywordsRegretPsychologySocial psychologyRomanceCounterfactual thinkingPerspective (graphical)Action (physics)Developmental psychologyInterpersonal communicationInterpersonal relationship

Abstract

fetched live from OpenAlex

Few sex differences in regret or counterfactual thinking are evident in past research. The authors discovered a sex difference in regret that is both domain-specific (i.e., unique to romantic relationships) and interpretable within a convergence of theories of evolution and regulatory focus. Three studies showed that within romantic relationships, men emphasize regrets of inaction over action (which correspond to promotion vs. prevention goals, respectively), whereas women report regrets of inaction and action with equivalent frequency. Sex differences were not evident in other interpersonal regrets (friendship, parental, sibling interactions) and were not moderated by relationship status. Although the sex difference was evident in regrets centering on both sexual and nonsexual relationship aspects, it was substantially larger for sexual regrets. These findings underscore the utility of applying an evolutionary perspective to better understand goal-regulating, cognitive processes.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.100
GPT teacher head0.387
Teacher spread0.287 · 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

Citations91
Published2006
Admission routes1
Has abstractyes

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