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Record W99773799

Cooperative Defence in Duet Singing Birds

2005· article· en· W99773799 on OpenAlexaff
David M. Logue

Bibliographic record

VenueSmithsonian Digital Repository (Smithsonian Institution) · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsSingingCommunicationPsychologyEcologyAdaptation (eye)Social psychologyBiology
DOInot available

Abstract

fetched live from OpenAlex

In many species of birds, pair mates sing duet songs. It has been hypothesized that coordinated singing is an adaptation to mediate conflict with rivals that would usurp territory or replace one of the pair mates. Duets should be more effective than solo songs at deterring rivals if duet songs signal that pair mates will defend cooperatively. While it has been argued that cooperative defence is incompatible with males pursuing their own fitness interests, counter arguments suggest several conditions in which cooperation may benefit both males and females. Data from observational studies of duetting birds provide some evidence of cooperative defence, but more quantitative studies are needed. Experimental removals of one pair mate have failed to demonstrate that being paired reduces the risk of territory loss. These experiments, however, have not been conducted over the relevant time scales and appear prone to Type II error. A meta-analysis of 19 song playback and decoy presentation experiments reveals that duetting species are significantly more cooperative (i.e. respond with a weaker same-sex bias) than nonduetting species. In summary, empirical evidence supports the hypothesis that duetting pair mates defend their territories and/or one another cooperatively, but fails to link cooperative defence to fitness benefits. KEY-WORDS: cooperation, sex roles, duetting, antiphonal song, tropical birds

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)0.002
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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

Citations47
Published2005
Admission routes1
Has abstractyes

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Same venueSmithsonian Digital Repository (Smithsonian Institution)Same topicAnimal Behavior and ReproductionFrench-language works237,207