Participatory Research in a School Setting: A Process of Acculturation
Bibliographic record
Abstract
This article describes a collaborative research study of university researchers and Grades one and two teachers from an Ontario, Canada French-language School Board. The School Board offered phonological awareness and reading-teaching training to grades one and two teachers with a long-term goal of improving the reading outcomes of the students in these classes. Researchers from University of Ottawa were asked to lead a collaborative research project on the impact of this training on the teacher's pedagogical approaches to teaching reading and ultimately the impact it had on their students. The objective of this article is to report the results of this collaborative research and more specifically to show the originality of SAS2 (social analysis systems) methodological tools, which mobilized a collective analysis and interpretation of perceptions on the training's impact. We also discuss the difficulties of doing collaborative research in a school setting, where traditional research is better known and expected.
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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 | 0.309 | 0.221 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.021 | 0.049 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".