Assessing emergency shelter patterns to inform community solutions to homelessness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The goal of this study was to examine individuals’ emergency shelter stay records to gain insight into cycles of homelessness and strategies to end homelessness. We examined over 46 000 records of 4332 unique individuals from six of Victoria, Canada’s adult emergency shelters from May 2010–May 2014. Individuals’ stay records were clustered using the k-means cluster analysis, based on total days stayed and total number of episodes of homelessness over the four-year period. Consistent with other Canadian cities, three significant clusters emerged from the analysis: temporary, episodic and long stay. The episodic and long-stay cluster accounted for more than 50 percent of shelter bed nights. Age and gender were analyzed, with seniors more likely to be represented in the long-stay cluster. These findings highlight the need for prevention and rapid re-housing initiatives for those experiencing temporary shelter use, and housing with intensive supports for those in the episodic and long-stay clusters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it