Neighbourhood change and women in social housing : the Oneesan container housing experience
Bibliographic record
Abstract
Project Focus and Objectives: This research project explores the micro-level impacts of neighbourhood changes on the lives of women living in Oneesan Container Housing, a supportive housing site in Vancouver’s Downtown East Side (DTES) Oppenheimer District (DEOD). Research Contributions: Academic literature often depicts gentrification as a linear and nearly homogenous pattern; this study provides a nuanced picture of gentrification impacts and neighbourhood change impacts at the neighbourhood and street levels. Findings on Neighbourhood Change: Three major neighbourhood changes have been noted in the years since Oneesan welcomed its first residents in 2013. First, the DTES Street Market has opened a new location at 501 Powell Street, on a lot that sits directly behind Oneesan. Second, there has been an increase in social housing in the neighbourhood, with over 380 units built since 2013. Finally, several new cafés and restaurants have opened in the neighbourhood. These businesses are perceived to mainly serve middle to upper class patrons, and are representative of larger gentrification processes in the DEOD neighbourhood. Findings on the Impacts of Neighbourhood Change: Through surveys, interviews and observations, it was found that the impacts and perceptions of neighbourhood changes were mixed. While the DTES Street Market serves as an economic opportunity for DTES residents, most of whom are struggling financially, it also poses concerns for Oneesan residents regarding illegal activities and the people the market will attract. The new social housing in the neighbourhood serves as a positive neighbourhood change, housing many vulnerable individuals on the DTES. Oneesan residents saw the benefit of this housing, but also expressed some minor concerns regarding the addition of new people to the neighbourhood. Correspondingly, some understood the new cafés and restaurants as a negative neighbourhood change, while one resident noted her enjoyment of one of these new businesses. Ultimately, these major neighbourhood changes take place within a wider context of social, economic and political forces. Considering recent changes in city planning policy, it is hypothesized that Oneesan’s neighbourhood will see even more changes in the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".