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Record W3111905254 · doi:10.1002/cjas.1588

La mesure du transfert des apprentissages: état des lieux et perspectives d'avenir pour la recherche

2020· article· en· W3111905254 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2020
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsUniversité du Québec en OutaouaisInstitut du Savoir MontfortUniversité de Sherbrooke
Fundersnot available
KeywordsDivergence (linguistics)Transfer of learningHumanitiesSociologyPolitical scienceLibrary sciencePsychologyComputer scienceArtPhilosophyDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Research on transfer of training (training transfer) has flourished in recent years. Given the absence so far of any comprehensive review of the various transfer measurement instruments used, a systematic review of research to date was performed. Three main findings emerged from the 51 studies reviewed: (1) there is a divergence between the definitions of transfer described in the studies and the concept of transfer reflected in the measurement instruments; (2) there are many different kinds of measurement instruments; and (3) scant information has been published on the parameters of the training whose transfer is being measured. In light of these findings, a research agenda is proposed for evaluating training transfer.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.007
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.370
GPT teacher head0.420
Teacher spread0.050 · 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