COMPLEXITÉ ET DÉFIS ASSOCIÉS AUX RÔLES DE CONSEILLER PÉDAGOGIQUE DES PALIERS D’ENSEIGNEMENT ÉLÉMENTAIRE ET SECONDAIRE
Bibliographic record
Abstract
Les conseillers pedagogiques des conseils et commissions scolaires accomplissent leur mission a travers une diversite de roles professionnels. A partir d’une recension d’ecrits et des temoignages de 11 conseillers pedagogiques oeuvrant dans un conseil scolaire francophone de l’Ontario, huit roles ont ete mis en lumiere. Par ailleurs, les defis rencontres par les participants dans l’exercice de chacun de ces roles ont ete explicites lors d’entretiens de recherche. Les enjeux particuliers associes notamment aux roles d’agent de changement, de praticien reflexif et de gestionnaire feront l’objet de la discussion. COMPLEXITIES AND CHALLENGES ASSOCIATED WITH THE ROLE OF PEDAGOGICAL ADVISOR Pedagogical advisors working at the school board level accomplish their mission by taking on a diversity of professional roles. A literature review and testimonials from 11 pedagogical advisors working for a francophone school board in Ontario highlight eight professional roles. The challenges faced by the participants while exercising each of these roles were further elaborated in research interviews. Specific issues associated to the roles of change agent, reflexive practitioner, and manager are further discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".