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Record W4210925471 · doi:10.1017/9781108347150.018

Socioecology of African Colobines

2022· book-chapter· en· W4210925471 on OpenAlexaff
Julie A. Teichroeb

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook-chapter
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsBiologyCONTESTDominance (genetics)Scramble competitionDominance hierarchyEcologyCompetition (biology)ZoologyAggressionPolitical scienceSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Formally, African colobines were not thought to be affected by food competition because mature leaves are relatively evenly distributed and low quality. However, greater research on colobus monkeys has shown that they have varied diets and rarely rely on mature leaves and that within-group scramble and both within- and between-group contest competition for food affects them. Within-group contest competition for resources may be seasonal but appears to be sufficient to lead to dominance hierarchies among females. These dominance hierarchies tend to be individualistic and females typically do not stay with kin to defend food. Unfortunately, there are still little data available to examine whether female dominance hierarchies lead to rank-effects on female energy intake or reproductive rates. In sum, African colobines do not seem fit current socio-ecological models and instead appear to fall somewhere between species with within-group scramble and within-group contest competition, where females disperse despite forming decided dominance relations. This appears to give rise to very specific male strategies, such as male defence of food resources, that may attract females and which alter female social strategies in interesting ways, changing social organization and structure.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.034
GPT teacher head0.251
Teacher spread0.217 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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