Scholas action program: modernizing and sustaining public schools in Quebec
Bibliographic record
Abstract
This chapter presents the transdisciplinary research and action program by the Schola consortium of researchers and partners to guide the modernization of public schools in the province of Quebec, Canada. This group of university professors-designers was mandated by the Quebec Ministry of Education to produce decision support tools based on reliable and credible knowledge, and to make those accessible via a web platform. The aging of Quebec’s school buildings and the evolution of the educational mandate has led to a favorable context for such research, to ensure that the renovations result in more functional, comfortable, pleasant, appropriable and sustainable schools, and support educational success. The team includes more than 100 researchers in architecture, design, and education. The research more broadly encompasses the ethical, technical, and aesthetic concerns of various stakeholders in the education community, ranging from the Ministry of Education, nearly 60 school boards, 1000 staff members in Quebec’s elementary and secondary schools, and 15 partner associations and federations. The chapter explains the challenges of simultaneously generating knowledge about specific schools and successfully generalizing it to a school population of over 2700 buildings located throughout the province of Quebec.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".