Urban Form, Everyday Life, and Ideology: Support for Privatization in Three Toronto Neighbourhoods
Bibliographic record
Abstract
One of the trends marking neoliberalism and the attack on the welfare state from the right is the move toward the privatization of public services. Recent research in both the United States and Canada suggests that residents of the suburbs of large urban regions are more likely to vote for political parties on the right and to support neoliberal policies such as privatization, while the opposite is true for inner-city dwellers. However, the reasons why such a spatial division should occur have received little academic attention. This paper seeks to fill this gap in the literature by analyzing the relationship between residential location, spatial factors, and attitudes toward privatization, using survey data collected in the Toronto region. Results suggest that the way urban space influences residents' daily routines and personal experiences may then mediate their perception of the uses of public services and the efficacy of government spending, factors which are found to affect spatial disparities in support of and/or in opposition to privatization. Thus, there is some evidence that urban spatial form is important for understanding the geographic unevenness of support for neoliberalism, and thus ultimately for the production of ideology.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".