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Record W2553578282 · doi:10.1075/la.235.01sci

The biolinguistics program

2016· book-chapter· en· W2553578282 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

VenueLinguistik aktuell · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à Montréal
Fundersnot available
KeywordsField (mathematics)Intersection (aeronautics)Relation (database)Object (grammar)Cognitive scienceComputer scienceHuman languageEpistemologyLinguisticsPsychologyArtificial intelligenceMathematicsPhilosophyEngineering

Abstract

fetched live from OpenAlex

The Biolinguistics Program is an emergent interdisciplinary field encompassing natural sciences, neurosciences and the humanities. Its core object of inquiry is human language. The overarching questions it raises are the following: what is language and what is the relation between language and biology. The central hypothesis it brings to the fore is that human language has a biological basis as well as unique traits that make language unique in the biological world. This paper details some of the specific questions and the hypotheses that have been formulated in this field, and it considers recent works on the intersection of language and biology. We start by stating the rationale for Biolinguistics. We then identify the questions and hypotheses raised by this field. Finally, we consider works that aim to bridge the explanatory gap between language and biology while preserving the unique properties of language.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.866
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.020
GPT teacher head0.311
Teacher spread0.292 · 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