Race, Space, and Media: The Production of Urban Neighbourhood Space in East-end Toronto
Bibliographic record
Abstract
In the last few decades, as Toronto neighbourhoods have become more diverse, they simultaneously have become more inequitable. Poverty and income disparity have increasingly become concentrated along neighbourhood lines. There is, however, little research on the discursive and experiential explorations of people living in these neighbourhoods and how these spaces are produced. This paper centers the culturalist constructions of space and its implications for racialized young people’s negotiations of belonging in an east-end Toronto ‘priority neighbourhood.’ Drawing on a critical framing analysis of newspaper discourses, this paper illustrates how young people who inhabit these spaces are differentially positioned. Through interview data, I examine how youth and youth service providers living in Malvern (a ‘priority neighbourhood’) negotiate production and representation of racialized spaces. Résumé: Au cours des dernières décennies, plus les voisinages de Toronto deviennent plus diversifiés, simultanément ils sont devenus inéquitables. La pauvreté et la disparité des revenus se concentrent de plus en plus le long des quartiers voisins. Il existe cependant peu de recherches sur les explorations discursives et expérientielles des personnes vivant dans ces villes voisines et sur la façon dont ces espaces sont conçus. Cet article se concentre sur les constructions culturalistes de l’espace et ses implications dans les négociations racialisées des jeunes occupant un « quartier prioritaire » du nord-est de Toronto. En se basant sur une analyse critique du recadrage des discours médiatiques, cet article illustre comment les jeunes qui habitent ces espaces sont différemment positionnés. À travers les données des entretiens, j’examine comment les jeunes et les prestataires de services pour les jeunes vivant à Malvern (un « quartier prioritaire ») négocient la production et la représentation d’espaces racialisés.
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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 | 0.002 |
| 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 | 0.001 |
| 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".