A simpler method for understanding emergency shelter access patterns
Bibliographic record
Abstract
The Simplified Access Metric (SAM) is a new approach for characterizing patterns of homelessness.The goal of SAM is to provide emergency shelter operators and housing staff with an intuitive way to understand a person or group's pattern of homelessness and/or shelter access that can be implemented by non-technical staff using spreadsheet operations.Client data from a large North American shelter will be used to demonstrate that SAM produces similar results to traditional transitional, episodic and chronic client cluster analysis.Since SAM requires less data than cluster analysis, it is also able to generate a timeline of homelessness patterns that can be updated in real time.Using nine years of shelter data, a shelter access timeline is presented that includes the introduction of Housing First programming and the COVID-19 lockdown.Finally, SAM allows shelter staff to move beyond assigning transitional, episodic and chronic labels and instead use the "soft" output of SAM directly to better understand a person's experience of homelessness.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".