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Record W2078717453 · doi:10.1086/339992

Understanding Reversals in the Relative Strength of Sexual Selection on Males and Females: A Role for Sperm Competition?

2002· article· en· W2078717453 on OpenAlexaff
Patrick D. Lorch

Bibliographic record

VenueThe American Naturalist · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSperm competitionSexual selectionCompetition (biology)BiologyOperational sex ratioFecunditySpermAffect (linguistics)MatingSelection (genetic algorithm)Mate choiceDemographyEcologyMating systemPsychologyPopulationGeneticsCommunication

Abstract

fetched live from OpenAlex

Sperm competition affects sexual selection intensity on males, but models suggest it cannot affect the relative intensity of sexual selection on males compared to females. However, if sperm competition depresses the payoff for male multiple mating, it could affect the relative intensity of sexual selection and even cause sexual selection to be more intense on females than males (reversal of typical pattern). To evaluate how sperm competition, energy availability, and parental investment affect the intensity of sexual selection on each sex, I constructed a simulation model using the relationship between fecundity and number of mates to estimate sexual selection gradients. Unlike earlier models, I include a trade-off between paternal investment and sperm competition ability. The amount of energy available for reproduction affects the sexual selection gradient for each sex. Reversals in the sex experiencing stronger sexual selection do occur when additional paternal investment reduces a male's ability to compete for fertilizations within females. The shape of the distribution of mates for each sex (determined by mate competition) is also important. Output from the model is qualitatively similar to empirical data from insects with paternal investment. This model challenges previous thinking about the role of sperm competition in sex-role reversal.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.141

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 head0.101
GPT teacher head0.279
Teacher spread0.178 · 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

Citations37
Published2002
Admission routes1
Has abstractyes

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