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Record W2374580303 · doi:10.25518/1782-2041.813

A plea for diachronic necessity: the case of language acquisition

2016· article· en· W2374580303 on OpenAlexaff
Vincent Grondin

Bibliographic record

VenueBulletin d Analyse Phénoménologique · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicWittgensteinian philosophy and applications
Canadian institutionsCegep Edouard Montpetit
Fundersnot available
KeywordsPleaIntuitionReading (process)EpistemologyInstinctPhilosophyLinguisticsPsychologyLaw

Abstract

fetched live from OpenAlex

According to a widespread reading of Philosophical Investigations, Wittgenstein’s conception of language relies on a substantial account of how language is actually learned by children.1 Originating from a set of papers written by Norman Malcolm (1954, 1982, 1989), this exegetical tradition has been prompted by several passages where Wittgenstein claims that our language is an “extension” and a “refinement” of our instinctive behaviours (PI §244, Z §454, CV p. 31, OC §538 and §204). Although Wittgenstein has always stressed the gulf lying between philosophical investigations and empirical sciences, these passages have moved a lot of scholars to draw the conclusion that Wittgenstein is actually committed to an implicit theory of language acquisition that should be taken into account in contemporary debates (HARRÉ & ROBINSON 1997, MOYAL-SHARROCK 2000). Among these ethologist readers of Wittgenstein, Canfield is probably the most radical: in a sequence of stimulating articles, he argues that ethological research should be conducted in accordance with Wittgenstein’s intuition about the learning language process (1993, 1995, 1996). This reading has, however, been seriously challenged for reasons that are mainly historical and exegetical (LOUGHLIN 2014, DROMM 2003, 2006). Among all objections encountered by the ethological reading of Wittgenstein, the most serious one is the fact that he states frequently that philosophy should not try to explain the genesis of concepts2 or to rec

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.999

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)0.0020.000

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 head0.022
GPT teacher head0.253
Teacher spread0.231 · 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 designTheoretical or conceptual
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

Citations0
Published2016
Admission routes1
Has abstractyes

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