MétaCan
Menu
Back to cohort
Record W4205449053 · doi:10.3390/languages7010005

Vocal Learning and Behaviors in Birds and Human Bilinguals: Parallels, Divergences and Directions for Research

2021· article· en· W4205449053 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguages · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsMcGill University
Fundersnot available
KeywordsParallelsPsychologyExperiential learningVocal learningLanguage acquisitionNeuroscience of multilingualismSocial learningContext (archaeology)Cognitive scienceCognitive psychologyCommunicationBiologyNeuroscience

Abstract

fetched live from OpenAlex

Comparisons between the communication systems of humans and animals are instrumental in contextualizing speech and language into an evolutionary and biological framework and for illuminating mechanisms of human communication. As a complement to previous work that compares developmental vocal learning and use among humans and songbirds, in this article we highlight phenomena associated with vocal learning subsequent to the development of primary vocalizations (i.e., the primary language (L1) in humans and the primary song (S1) in songbirds). By framing avian “second-song” (S2) learning and use within the human second-language (L2) context, we lay the groundwork for a scientifically-rich dialogue between disciplines. We begin by summarizing basic birdsong research, focusing on how songs are learned and on constraints on learning. We then consider commonalities in vocal learning across humans and birds, in particular the timing and neural mechanisms of learning, variability of input, and variability of outcomes. For S2 and L2 learning outcomes, we address the respective roles of age, entrenchment, and social interactions. We proceed to orient current and future birdsong inquiry around foundational features of human bilingualism: L1 effects on the L2, L1 attrition, and L1<–>L2 switching. Throughout, we highlight characteristics that are shared across species as well as the need for caution in interpreting birdsong research. Thus, from multiple instructive perspectives, our interdisciplinary dialogue sheds light on biological and experiential principles of L2 acquisition that are informed by birdsong research, and leverages well-studied characteristics of bilingualism in order to clarify, contextualize, and further explore S2 learning and use in songbirds.

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.

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 score0.511
Threshold uncertainty score0.182

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 head0.071
GPT teacher head0.452
Teacher spread0.381 · 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