Individual well-being as a function of place among clients of residential addictions treatment facilities in Winnipeg
Bibliographic record
Abstract
This study evaluates place-based social and material networks that are thought to influence individual well-being, as they relate to the sfudy population, clients of residential addictions treatment facilities in Winnipeg.This research is parr of a more general consideration of the health affects of facility siting.Without any serious inquiry into the envilonments of existing addictions treatment facilities, their influence on clients' well-being, and the land-use policies which govern their existence and location, we are not only ignoring the potential for creating a more useful understanding of our health ïesources, but potentially entrenching existing social-spatial inequities.A cross-sectional case study, using a survey questionnaire was used to explore potential links between individual health and facility location.This quantitative analysis of place-based influences on health considers data on thirty-two clients, fi-om tlree addictions treatment programs, located in three distinct neighbourhoods in Wimtipeg.The study findings provide evidence that facility location is linked to various place-based social and material networks, which are associated with indicators of individual well-being.The niethodology employed in this study may be relevant to those, especially urban planners, with an interest in exploling the inter-relationship betweerr well-being and the sociaVbuilt envilonment and/or in evaluating the siting of health facilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".