Where worlds collide : social polarisation at the community level in Vancouver's Gastown/Downtown Eastside
Bibliographic record
Abstract
Gastown, Vancouver's birthplace, is a small historic district embedded within the broader community of the Downtown Eastside. Over the past 25 years Gastown has been slowly upgrading; refashioning itself as a loft style residential neighbourhood and central tourist destination. Over the same period the Downtown Eastside's reputation as the city's "skid road" has become firmly entrenched. The pace of this community's upgrading and downgrading has quickened over the past five years and resulted in a current geography where we find loft-style condominiums, cappuccino bars and rising affluence interspersed with needle exchanges, homeless shelters and deepening disadvantage. What we see within the Gastown/Downtown Eastside community is a convergence of the spatial processes of social polarisation and the kinds of conflicts and negotiations that result. Polarisation, most broadly defined, describes a growing socio-economic and spatial divide between the "haves" and "have-nots" of Western societies and cities. While considerable attention has been paid to polarisation's conceptual meaning and empirical definition at the national and intra-urban levels, little focus has centered on how the process can be identified and analysed at the intra-community level. In the same way that polarisation at broader scales of analysis can be viewed as the sociotemporal coincidence of pauperisation and professionalisation, this dissertation defines intracommunity polarisation as the simultaneous occurrence of socio-spatial upgrading and downgrading. Using quantitative data from the census tract level, this dissertation investigates the empirical evidence of social polarisation within Gastown/Downtown Eastside. Using qualitative data the study explores the extent to which both revitalisation and deterioration are competing for the community's future and this polarisation is being experienced and negotiated by the varied residents and stakeholders of this urban community. Ultimately this dissertation sheds light on how the characteristics and causes of community based polarisation differ and parallel those at other scales of inquiry. It also outlines the truly local factors that affect polarisation's development, entrenchment and impact and illuminates the process' inconstant character and the time lag that exists between its qualitative experience and its quantitative identification.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.019 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.004 |
| 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".