Territorial Stigma on the Canadian Prairies: Representations of North Central, Regina
Bibliographic record
Abstract
The community of North Central, located within the small prairie city of Regina, Saskatchewan in Canada, is known for high crime rates, poor socioeconomic conditions and a large concentration of Aboriginal residents. The area’s negative reputation was furthered when MacLean’s magazine named it “Canada’s Worst Neighbourhood” in 2007. The goal of this research is to offer a richer context for this "reputation" by investigating North Central as a stigmatized territory. Territorial stigma has harmful effects (i.e. negatively impacts the social, economic, physical and mental wellbeing of residents) and as such, the role of representation and stigma must be analyzed so that inequality between neighbourhoods may be addressed proactively. This research project asks: how do residents and non-residents reproduce and resist dominant representations of North Central, Regina? This question is investigated through the analysis of fifteen semi-structured interviews using NVivo qualitative research software and Attride-Stirling’s thematic network analysis. The analysis revealed three global themes: 1) North Central is a socially constructed location and concept; 2) representations in the news media and 3) interpersonal representations. This thesis reveals that both residents and non-residents of North Central acknowledge that North Central is a troubled inner-city neighbourhood but participants tend to both challenge and emphasize various aspects of North Central, sometimes reproducing dominant representations of North Central even while trying to resist them. This research provides a greater understanding of the complex social construction of dominant representations of stigmatized urban communities.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".