COVID-19 and the Homelessness Support Sector
Bibliographic record
Abstract
This exploratory study sought to uncover service provider perspectives on the early response to COVID-19 in a small community in an advanced industrialized country - the homelessness support sector of the Central Okanagan, British Columbia. Following a case study approach, snowball sampling was utilized in May and June 2020 to achieve a sample size of 30 through a mix of one-on-one interviews and open-ended surveys. Qualitative thematic analysis was used to uncover commonalities among interview responses. Common themes are discussed in relation to three areas of questioning including challenges, successes, and mitigations/areas for future support. While the community came together to support the response, there were challenges and concerns regarding safety and personal protective equipment supplies, social distancing and knowledge transmission within the homeless community, access to food and water, and lack of space for isolating positive cases. The findings illustrate possible research, practice, public health policy, and emergency planning considerations within smaller communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 teacher head, 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".