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Record W6945695018 · doi:10.25656/01:12079

Contextes de formation formel, non formel ou informel: développement de compétences de direction d’école de langue française au Canada

2014· article· fr· W6945695018 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenuepeDOCS · 2014
Typearticle
Languagefr
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Power (physics)ESPACEHomogeneous

Abstract

fetched live from OpenAlex

Pour parfaire les compétences des nouvelles directions d’école, nous constatons l’émergence de programmes de formation proposés par des universités, des districts scolaires, etc. Le but de notre étude est d’identifier les contextes de formation formel, non formel ou informel qui ont le plus aidé les nouvelles directions d’école dans le développement de leurs compétences d’une part, et ceux qui seraient mieux à même de les aider à l’avenir. Dans le cadre de cette recherche qualitative, 101 acteurs-trices de l’éducation ont été interrogé-es. Les résultats montrent que les trois contextes de formation (formel, non formel et informel) semblent avoir contribué au développement des compétences des nouvelles directions, alors que le contexte non formel, et plus particulièrement les ateliers et le soutien du district scolaire, s’avère être celui pouvant le plus aider les nouvelles directions à développer leurs compétences dans le futur. (DIPF/Orig.)

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.007
GPT teacher head0.248
Teacher spread0.242 · 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