Electoral politics, gentrification, and strategic use of contested place identities in Toronto’s Portuguese neighbourhood
Bibliographic record
Abstract
This article uses the lens of electoral politics to improve understanding of political dynamics in an ethnic neighbourhood undergoing gentrification, corresponding to Ward 18 and its antecedents in the City of Toronto. This ward has been populated by Portuguese immigrants and their descendants since the 1960s. Since the 1990s, gentrification has corresponded to a decrease in the Portuguese population alongside a proliferating, diverse mix of new arrivals. This article tackles the question of how gentrification affects electoral politics in this traditionally ethnic neighbourhood. In the history of Toronto’s municipal elections, a first-generation Portuguese Canadian candidate first appeared on the ballot in 1978; a decade later, the ward elected another first-generation Portuguese Canadian to the city council. In 2014, the third and most recent of them pursued her candidacy while recognizing the changed demographic and cultural circumstances of the neighbourhood existing as two places within a single urban space. Competing against a candidate with no cultural affiliation to the Portuguese Canadian community, the incumbent won by a narrow margin through appealing to out-group residents, while respecting and cherishing the Portuguese residents, or her robust electoral base. This electoral mirroring of the current condition of this urban space has implications for understanding the relationships between gentrification, urban ethnic minorities, and electoral politics; ethnicity is consolidated through electoral campaigns and mobilized as a useful and handy political tool, and both ethnic-based and non–ethnic-based place identities are strategically utilized for electoral politics in an ethnic neighbourhood undergoing gentrification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".