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Record W4389339479 · doi:10.4324/9781003190912-24

De-generacy as an Organizing Principle of Bilingual Language Processing

2023· book-chapter· en· W4389339479 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLanguage, Communication, and Linguistic Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsLinguisticsComputer scienceArtificial intelligenceNatural language processingPhilosophy

Abstract

fetched live from OpenAlex

It is well recognized in cognitive science that people differ in their language abilities, where even those who appear to behave similarly can reach the same outcome via different strategies and neural correlates. At the same time, recent discoveries have emphasized the mediating role of interactional contexts in shaping language experience and their effects on language performance. This chapter adds to this work by illustrating how variability in language use, processing, and experience reveals fundamental insights into the evolutionary and ecological forces that shape dynamic and adaptive changes in language and control networks. To do so, the system property of de-generacy is presented as a valuable explanatory tool to conceptualize a key organizing principle of complex adaptive systems and to offer new understanding of behavioral and neurocognitive variability in language learning and processing in monolingual and bilingual speakers.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.762
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.384
Teacher spread0.331 · 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