The new articulation of equity education in neoliberal times: the changing conception of social justice in Ontario
Bibliographic record
Abstract
In this paper, we draw attention to the impact of neoliberal globalisation in rearticulating conceptions of equity within the Ontario context. The Ontario education system has been hailed for its top performance on Programme for International Student Assessment (PISA) as a high-equity/high-quality education system and created ‘PISA envy’ in the international context. Our aim in this paper is to provide some critical analysis of the neoliberal rationality and to examine its manifestations for rearticulating conceptions of social justice. Drawing on equity education policies in Ontario and one in-depth interview with an equity practitioner in one of Ontario’s large and most diverse school boards, this paper illustrates how a redefinition of equity has been made possible through neoliberal systems of accountability and performativity involving measurement and facticity. As a result of these strategies, equity policy in education has been concerned with outcome measurement and boys’ underachievement, while racial and class inequalities have become invisible. While this paper is focused on Ontario equity policy, we believe that it serves much broader interest given the current context of global education policy field.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.027 | 0.053 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".