MétaCan
Menu
Back to cohort
Record W1771881231 · doi:10.22330/001c.89784

Women’s Competition for Mates: Experimental Findings Leading to Ethological Studies

2015· article· en· W1771881231 on OpenAlexaff
Maryanne L. Fisher

Bibliographic record

VenueHuman Ethology · 2015
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsCompetition (biology)CovertSexual selectionContext (archaeology)PsychologySocial psychologyDevelopmental psychologyEcologyHistoryBiology

Abstract

fetched live from OpenAlex

There has been an explosion of survey-based and experimental work pertaining to women’s intrasexual competition for mates. Rather than extensively review this growing and vast body of literature, the goal of this paper is instead to call for ethological studies on this topic. I propose that, in general, non-ethological studies should cause us to question the reliability of findings, how frequently, and in what contexts competitive strategies are used. After a condensed overview of the evolutionary theory of female intrasexual competition, the paper is organized around three central problems that are faced by researchers who want to use an ethological approach. First, I will briefly review how female intrasexual competition involves multiple strategies that are often indirect or covert. Second, I will discuss how female intrasexual competition is dynamic, and changes depending on particular variables, such as hormonal status and audience. Third, I will argue that the context for examining competition matters, such that the reach of competitive views and attitudes is far wider than previously considered. I support this third point by presenting the results of a preliminary study where women appeared to engage in competition after merely being primed to think about potential threats to their romantic relationships.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.352
GPT teacher head0.503
Teacher spread0.150 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations52
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueHuman EthologySame topicEvolutionary Psychology and Human BehaviorFrench-language works237,207