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Record W2213655925 · doi:10.1111/eth.12447

Coalition Formation by Male Vervet Monkeys (<i><scp>C</scp>hlorocebus pygerythrus</i>) in <scp>S</scp>outh <scp>A</scp>frica

2015· article· en· W2213655925 on OpenAlexafffund
Natalie J. Freeman, Christopher Young, Louise Barrett, S. Peter Henzi

Bibliographic record

VenueEthology · 2015
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaNational Research Foundation
KeywordsCONTESTAggressionMatingHaremBiologyDemographyZoologyEcologyPsychologySocial psychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

Abstract Unrelated male primates frequently cohabit in bisexual groups and, despite being reproductive competitors, have been shown to cooperate in ways that are associated with reproductive success. Such coalitions between males are common in some taxa, where they can serve two primary functions – status management and improved mating opportunities – that subserve long‐ and short‐term objectives. Here, we use observational data to provide information on male coalitions in vervet monkeys ( Chlorocebus pygerythrus ), a guenon with a multimale group structure. We recorded a total of 62 coalitions from two troops across a 10‐mo period at Samara Game Reserve, South Africa. We found that males who were more frequently associated spatially and who had groomed one another were more likely to form coalitions and did so against higher‐ranking opponents. This was not linked to any evidence that coalitionary aggression provided either short‐ or long‐term reproductive benefits for the aggressors and coalitions were not restricted to the mating season. There was little evidence that particular individuals were targeted, reciprocation between partners was not observed, and recent immigrant males were not targeted disproportionately. Our data suggest that within‐group coalition formation between vervet males may represent something close to an ancestral state whereby males form ad hoc coalitions opportunistically, joining an ongoing dyadic contest to target an opponent without facing the possible risks of dyadic contest, such as a greater chance of injury.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.005

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 head0.051
GPT teacher head0.318
Teacher spread0.267 · 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.

Study designNot applicable
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

Citations13
Published2015
Admission routes2
Has abstractyes

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