MétaCan
Menu
Back to cohort
Record W1963796658 · doi:10.1017/s0140525x08005025

Languages as evolving organisms –<i>The</i>solution to the logical problem of language evolution?

2008· article· en· W1963796658 on OpenAlexaff
Christina Behme

Bibliographic record

VenueBehavioral and Brain Sciences · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsDalhousie University
Fundersnot available
KeywordsArgument (complex analysis)Focus (optics)CognitionGrammarUniversal grammarCognitive scienceLogical conjunctionInclusion (mineral)Computer scienceLinguisticsEpistemologyPsychologyPhilosophyBiologySocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

Abstract Christiansen &amp; Chater (C&amp;C) argue persuasively that Universal Grammar (UG) could not have arisen through evolutionary processes. I provide additional suggestions to strengthen the argument against UG evolution. Further, I suggest that C&amp;C's solution to the logical problem of language evolution faces several problems. Widening the focus to mechanisms of general cognition and inclusion of animal communication research might overcome these problems.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.037
GPT teacher head0.343
Teacher spread0.306 · 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.

Study designQualitative
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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueBehavioral and Brain SciencesSame topicLanguage and cultural evolutionFrench-language works237,207