Editorial: Mini-special issue on Bill 23
Bibliographic record
Abstract
This issue is unique in more than one way.It is the second of our general issues containing a mini-special issue.And this mini-special issue is truly distinctive, unprecedented even in journal annals, in being the result of a shared concern and simultaneous call across three education journals in Quebec: Revue des sciences en l'ducation, Formation et profession, and the McGill Journal of Education/Revue des sciences de l'ducation de McGill (MJE/RSEM).The call invited authors to reflect on the implications, locally and internationally, of Quebec's Bill 23 (now law), with its greater concentration of powers in the Minister of Education and its accelerated streamlining of teacher preparation.The lead special editors on this minispecial issue at the MJE/RSEM were Simon Collin (UQAM), Genevive Sirois (Universit TELUQ), and Paul Zanazanian (McGill).In their mini special issue editorial, they further explain the issue's focus as well as introduce the three featured articles.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".