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Record W2145405281 · doi:10.1098/rstb.2011.0223

Social networks and the development of social skills in cowbirds

2012· article· en· W2145405281 on OpenAlexaff
David J. White, Andrew S. Gersick, Noah Snyder‐Mackler

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSocial skillsSocial changeBiologyEvolutionary biologyPsychologySociologyDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

The complex interrelationships among individuals within social environments can exert selection pressures on social skills: those behaviours and cognitive processes that allow animals to manipulate and out-reproduce others. Social complexity can also have a developmental effect on social skills by providing individuals with opportunities to hone their skills by dealing with the challenges posed in within-group interactions. We examined how social skills develop in captive, adult male brown-headed cowbirds (Molothrus ater) that were exposed to differing levels of 'social complexity' across a 2-year experiment. After each year, subjects housed in groups with dynamic social structure (where many individuals entered and exited the groups during the year) outcompeted birds who had been housed in static groups. Exposure to dynamic structure subsequently led to substantial changes to the social networks of the home conditions during the breeding season. Static groups were characterized by a predictable relationship between singing and reproductive success that was stable across years. In dynamic conditions, however, males showed significant variability in their dominance status, their courting and even in their mating success. Reproductive success of males varied dramatically across years and was responsive to social learning in adulthood, and socially dynamic environments 'trained' individuals to be better competitors, even at an age when the development of many traits important for breeding (like song quality) had ended.

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)0.001
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 score0.436
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.053
GPT teacher head0.315
Teacher spread0.262 · 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

Citations32
Published2012
Admission routes1
Has abstractyes

Explore more

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