Using Institutional Structures to Promote Educational Equity
Bibliographic record
Abstract
This article traces diverging trajectories in a situated, participatory research project in 2 public schools in Ontario. While the project operated within a consistent set of objectives to promote educational equity for immigrant, linguistically diverse students and their families, it generated 2 substantially different models of educational provision at each of the 2 schools: one corresponding to the enrichment approach the project envisioned and the second to a remediation strategy grounded in an institutional discourse of deficit. The problematic we elucidate here is how such diverging outcomes could have been engendered. We begin by describing the conceptual bases for the activist research agenda; we then outline the interventionist, literacy enrichment framework of the project; next, we describe how the project took shape at the 2 research sites; and, finally, our reflective turn at the conclusion of this article represents our best effort to make sense of these contradictory experienced realities.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.050 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".