The provision of dental care to emergency shelter users corresponds to lower shelter use over time among typical users
Bibliographic record
Abstract
Using linked data from emergency shelters and a dental program in Canada, we sought to determine whether dental care is associated with fewer emergency shelter stays in this retrospective cohort study. We can observe when an individual accessed free dental care and how emergency shelter use changed over four years of follow-up, matching participants to comparable controls. We estimate difference-in-differences effects for each year since receipt of dental care. We estimate models for the typical user (M-estimation) and the average user (OLS regression). We found that in years 2, 3, and 4 after care, the typical user experienced a net result of fewer shelter stays than controls. The estimated average user stayed more nights in shelter than controls over the four years after dental care, likely driven by outliers that used substantially more shelter stays than the typical user. These results are consistent with the idea that participants benefit in the long-term from dental care received while at an emergency shelter after an initial stabilization period. That is likely due to both the permanent nature of the intervention and the lack of access to publicly-funded dental care in Canada.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".