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Record W2137802497 · doi:10.1017/s1366728908003337

Bilingual effects are not unique, only more salient

2008· article· en· W2137802497 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

VenueBilingualism Language and Cognition · 2008
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsSalientEmotionalityNeuroscience of multilingualismPsychologyCognitive psychologyLinguisticsDomain (mathematical analysis)Social psychologyComputer scienceMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

I am in full agreement with Aneta Pavlenko's analysis of the data and her line of reasoning about emotion words and emotion concepts, but not with her claim that the findings are unique to the study of bilingualism, and that differential language emotionality is uniquely visible in bi- and multilingual speakers. I will argue that (i) emotion words and concepts behave like other aspects of bilingualism, exhibit the same kinds of phenomena, and are susceptible to the same types of interference; (ii) the phenomena observed about emotion words and emotion concepts are not unique to bilinguals but merely more salient; and (iii) what applies in any conceptual domain applies within the emotion domain as well, in both unilinguals' and bilinguals' conceptual systems.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score1.000

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)0.0010.000

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 head0.018
GPT teacher head0.304
Teacher spread0.287 · 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