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Record W2465467661 · doi:10.1111/ele.12621

The ecology of sex explains patterns of helping in arthropod societies

2016· article· en· W2465467661 on OpenAlexfundno aff
Nicholas G. Davies, Laura Ross, Andy Gardner

Bibliographic record

VenueEcology Letters · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersClarendon FundNatural Sciences and Engineering Research Council of CanadaNatural Environment Research CouncilSight Research UK
KeywordsEcologyArthropodBiologyEvolutionary ecologyHost (biology)

Abstract

fetched live from OpenAlex

Across arthropod societies, sib-rearing (e.g. nursing or nest defence) may be provided by females, by males or by both sexes. According to Hamilton's 'haplodiploidy hypothesis', this diversity reflects the relatedness consequences of diploid vs. haplodiploid inheritance. However, an alternative 'preadaptation hypothesis' instead emphasises an interplay of ecology and the co-option of ancestral, sexually dimorphic traits for sib-rearing. The preadaptation hypothesis has recently received empirical support, but remains to be formalised. Here, we mathematically model the coevolution of sex-specific helping and sex allocation, contrasting these hypotheses. We find that ploidy per se has little effect. Rather, the ecology of sex shapes patterns of helping: sex-specific preadaptation strongly influences who helps; a freely adjustable sex ratio magnifies sex biases and promotes helping; and sib-mating, promiscuity, and reproductive autonomy also modulate the sex and abundance of helpers. An empirical survey reveals that patterns of sex-specific helping in arthropod taxa are consistent with the preadaptation hypothesis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.278
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.198
Teacher spread0.175 · 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.

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

Citations31
Published2016
Admission routes1
Has abstractyes

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