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Record W2081966532 · doi:10.1086/512107

Spiteful Soldiers and Sex Ratio Conflict in Polyembryonic Parasitoid Wasps

2007· article· en· W2081966532 on OpenAlexaff
Andy Gardner, Ian C.W. Hardy, Peter Taylor, Stuart A. West

Bibliographic record

VenueThe American Naturalist · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsSelfishnessAltruism (biology)BiologyInterpretation (philosophy)CasteCompetition (biology)PolyembryonyEvolutionary biologySocial psychologyEcologyPsychologyGeneticsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

The existence of spiteful behaviors remains controversial. Spiteful behaviors are those that are harmful to both the actor and the recipient, and they represent one of the four fundamental types of social behavior (alongside selfishness, altruism, and mutual benefit). It has generally been assumed that the conditions required for spite to evolve are too restrictive, and so spite is unlikely to be important. This idea has been challenged in recent years, with the realization that localized competition can relax the conditions required for spite to evolve. Here we develop a theoretical model for a prime candidate for a spiteful behavior, the production of the sterile soldier caste in polyembryonic wasps. Our results show that (a) the biology of these soldiers is consistent with their main role being to mediate conflict over the sex ratio and not to defend against competitors and (b) greater conflict will occur in more outbred populations. We also show that the production of the sterile soldier caste can be classed as a spiteful behavior but that, to an extent, this is merely a semantic choice, and other interpretations such as altruism or indirect altruism are valid. However, the spite interpretation is useful in that it can lead to a more natural interpretation of relatedness and facilitate the classification of behaviors in a way that emphasizes biologically interesting differences that can be empirically tested.

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 score0.597
Threshold uncertainty score0.577

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 head0.024
GPT teacher head0.244
Teacher spread0.220 · 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

Citations101
Published2007
Admission routes1
Has abstractyes

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