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Record W1977325242 · doi:10.1037/a0015414

The importance of development: What songbirds can teach us.

2009· review· en· W1977325242 on OpenAlexafffund
Scott A. MacDougall‐Shackleton

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsVocal learningPsychologyDevelopmental psychologyAffect (linguistics)StressorCognitive psychologyCommunicationNeuroscience

Abstract

fetched live from OpenAlex

Birdsong is a sexually selected signal that is learned early in life. Song learning (imitative vocal learning) by male songbirds has been extensively studied, but other aspects of development are important in birdsong as well. Female experience with song can affect song preferences in some species but not in others. The neural responses to song in females, as assessed by immediate-early gene expression, likewise appear related to early learning in some studies but not others. The development of song preferences by females requires further study to determine how genes interact through experience to produce adult preferences. Male song learning appears to be affected by exposure to environmental stressors during development. Developmental stressors impair both neural development and song learning. Thusly female song preferences may guide females to mate with males who have had benign developmental conditions and/or high developmental stability. These lines of research highlight the importance of considering development whether examining the function or the mechanisms of behaviour.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.070
GPT teacher head0.371
Teacher spread0.301 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentaleSame topicAnimal Vocal Communication and BehaviorFrench-language works237,207