The Criminalization of Homelessness in British Columbia: The BC Safe Streets Act
Bibliographic record
Abstract
The BC Safe Streets Act (BCSSA) criminalizes certain types of panhandling activities, including aggressive solicitation and captive audience solicitation. Given that panhandling is primarily a trade of people experiencing homelessness and extreme poverty, the primary objective of this project was to determine whether the costs of the BCSSA outweigh its benefits. This question was answered through a mixed-methods approach, utilizing qualitative data from a jurisdictional scan and literature review and quantitative data gathered through Freedom of Information requests (FOIs) to police departments across BC, as well as ICBC. The primary positive outcomes stemming from the BCSSA and similar legislation were related to reductions in problematic panhandling activity over temporally and geographically limited contexts. The negative outcomes stemming from the BCSSA and similar legislation were poor physical, social, and economic outcomes for those criminalized under the regime, significant debt burden placed on economically vulnerable populations, exacerbation of stigmatization leading to deeper entrenchment in homelessness and poverty, community rejection of support- and service-oriented policies, and a lack of evidence of long-term effectiveness. Ultimately, the most important recommendation that emerged from this research was that the Attorney General and Minister responsible for Housing should immediately repeal the BCSSA and instead address panhandling through evidence-based policies that address its root causes - poverty and homelessness.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".