CONFLICTING VISIONS, COMPETING EXPECTATIONS: CONTROL AND DE-SKILLING OF EDUCATION - A PERSPECTIVE FROM ONTARIO
Bibliographic record
Abstract
ABSTRACT. This article examines recent Ontario Government regulations that have had a far-reaching impact on the working conditions and job expectations of Ontario teachers. The article explores the restructuring initiatives in education that are associated with these regulations. It argues that although the changes have been promoted in the name of excellence and quality enhancement, in fact, they have destabilized the public school system, resulted in de-skilling of teachers, and may ultimately facilitate inroads into education by the private sector. POINTS DE VUE DISCORDANTS, ATTENTES CONTRADICTOIRES: UNE PERSPECTIVE ONTARIENNE SUR LE CONTROLE ET LA DEQUALIFICATION DE L'EDUCATION RESUME. Cet article analyse les recents reglements edictes par le gouvernement de l'Ontario qui ont eu un profond retentissement sur les conditions de travail et les perspectives d'emploi des professeurs de l'Ontario. L'article analyse les initiatives de restructuration dans l'education qui se rattachent a ces reglements. L'auteur affirme que meme si les changements ont ete preconises au nom de l'excellence et de l'amelioration de la qualite, ils ont, en fait, destabilise le reseau scolaire public et entraine la dequalification des professeurs, risquant peut-etre ainsi de faciliter les incursions du secteur prive dans le secteur de l'education.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.027 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".