Conducting Research on Homelessness in Canada from a Community Psychology Perspective: Reflections on Lessons Learned
Bibliographic record
Abstract
Homelessness has emerged as a significant and enduring social problem globally in developing and developed countries. With is aim of promoting social justice and influencing public policy, community psychology has much to offer in terms of addressing this problem. The presentation will focus on research and on research and knowledge mobilization efforts on homelessness in Canada of the keynote speaker that now spans over a decade. Specifically, findings from intervention and observational studies as well as knowledge dissemination products including a short video and report card on homelessness will be presented. Lessons learned from this work as a community psychologist will be discussed.
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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 | 0.061 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.049 | 0.027 |
| Scholarly communication | 0.020 | 0.007 |
| Open science | 0.008 | 0.015 |
| Research integrity | 0.010 | 0.023 |
| 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".