Neoliberal Urbanism and the Assault Against Public Services and Workers in Toronto, 2006-2011
Bibliographic record
Abstract
This article explores demands for concessions from public sector workers and new pressures to privatize public services at the city of Toronto. Situated in historical perspective, I argue that through the 2009 round of bargaining between the City of Toronto and its civic workers, the City sought to shift the burden of recession onto unionized workers by positing a trade-off between wage restraint and the protection of public services. Rather than retreat from the neoliberal project or present an alternative developmental path in the face of declining revenues, the ‘Third Way progressivism’ of the Miller regime employed the rationale that the recession demanded austerity. In the absence of an alternative political program and engaged membership, Local 79 was unable to counter the drumbeats of austerity and retrenchment. In the subsequent election a new conservative mayor and council vowed to radically restructure the city along increased competitive pressures, with efforts to lower the wages and benefits of its public sector workforce and privatize city services and assets. Indeed, since the 2009 civic workers’ strike, the Ford administration has implemented a number of reforms which has made work more precarious, reduced access to city services and intensified fiscal pressures. In the absence of a collective capacity to resist such attacks, trade union and community activists in Toronto have much to be concerned about.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".