Understanding and eliminating regulatory barriers to market entry in the DTES
Bibliographic record
Abstract
This Project examines the complex economic, political, and social factors that drive the informal economy in the Downtown Eastside (DTES) of Vancouver, British Columbia, Canada. The stagnation in welfare rates coupled with the lack of policy interventions has prevented the DTES community from pulling itself out of poverty and social exclusion. Using the theory of social innovation, this paper provides policy recommendations that can support the informal workforce and social enterprises in the DTES—which has the potential to make a significant contribution to poverty alleviation in the city of Vancouver. The socioeconomic characteristics and structure of DTES’s informal economy is explored using three ongoing socially innovative projects in partnership with the Local Economic Development Lab (LEDlab)—The Binners’ Project, DTES Street Market, and Knack. These nonprofit social enterprises are currently providing opportunities for social integration and economic development for DTES residents who have been working within the informal economy. My project presents an opportunity for the City of Vancouver to engage, integrate, and build capacity among those that have limited economic options, who in turn can contribute to an equitable socioeconomic regeneration of the urban environment.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".