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Record W2943029631 · doi:10.11621/vsp.2019.01.174

Methodological issues of studying the impact of bilingualism on cognitions and ethnocultural identity.

2019· article· en· W2943029631 on OpenAlexfundno aff
Ludmila A. Chaiguerova, Alexandra G. Dolgikh, Olesya Savelyeva

Bibliographic record

VenueMoscow University Psychology Bulletin · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
FundersUniversity of OxfordMcGill University
KeywordsNeuroscience of multilingualismIdentity (music)PsychologyCognitionArtAesthetics

Abstract

fetched live from OpenAlex

МЕтОдОЛОГИчЕСкИЕ ПрОБЛЕМы ИССЛЕдОВАНИЯ ВЛИЯНИЯ дВуЯЗычИЯ НА кОГНИтИВНыЕ ПрОцЕССы И этНОкуЛьтурНую ИдЕНтИчНОСть ю

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.093
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.093
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.159
GPT teacher head0.379
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations9
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueMoscow University Psychology BulletinSame topicLinguistics, Language Diversity, and IdentityFrench-language works237,207