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On the History of Universal Grammar

2016· reference-entry· en· W2594349873 on OpenAlexaff
James McGilvray

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSketchUniversal grammarGrammarNatural (archaeology)Natural scienceLinguisticsGenerative grammarNatural languageTuringComputer scienceEpistemologyPhilosophyHistoryProgramming language

Abstract

fetched live from OpenAlex

As with other technical natural science terms, ‘Universal Grammar’ or ‘UG’ is defined not by ordinary usage, but within a science. While the methodological foundations (where to look, and how) of the natural science of language were laid in the 17th century, it is only with the advent of formal tools due to Church, Turing, and others in the 1930s and the efforts of Chomsky from the 1950s on that that science came to fruition. In this chapter, I outline the brief history of the technical term UG and assess the progress of the natural science of language. And as Chomsky does in his ‘Cartesian Linguistics,’ while acknowledging Descartes’s many errors, I sketch his lasting contributions to natural science method and to the nativist and internalist scientific study of the mind.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.488
Threshold uncertainty score0.975

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)0.0260.000

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 head0.040
GPT teacher head0.212
Teacher spread0.172 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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