Negotiating Acts of Citizenship in an Era of Neoliberal Reform: The Game of School Closures
Bibliographic record
Abstract
Abstract In Ontario, the landscape of public education has changed quite rapidly during the past decade. Critics argue that neoliberal policies concerning privatization and marketization in the education system have produced different outcomes for different groups. One of the most sensitive issues during these years has been the closure of schools. Over three years (1999–2002) nearly 200 schools were closed in Ontario. These many changes, however, have not gone uncontested and communities have adapted to these circumstances in different ways. Acts of citizenship range from coping independently to challenging these changes collectively. This article examines the failures and successes of various acts of citizenship in challenging neoliberal governmental rationalities. More specifically, it traces the difficult process of school closure negotiations using examples from Toronto. Based primarily on participant observation carried out over a year, it examines the politics of the community consultation process among a heterogeneous ‘family of schools’ amid mixed incomes and varying capacities and needs. Through these case studies it explores whether these acts are inclusionary or exclusionary, homogenizing or diversifying, positive or negative. The evolution of the planning process is examined at three different periods (1998, 1999, 2000), demonstrating the slow and steady construction, advancement and legitimization of neoliberal policy, and correspondingly the spaces and citizens it makes and unmakes through this process. The article concludes with a framework of collective action highlighting relational aspects of citizenship that lead to positive or negative consequences for civil society.
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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 | 0.029 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.113 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".