A Canadian Community-University Research Alliance: Focus on Poverty and Social Inclusion for Psychiatric Consumer-Survivors
Bibliographic record
Abstract
This commentary serves as a snapshot of a study midway through data collection and outlines some preliminary results. The purpose of the study is to better understand inter-relationships between poverty and social inclusion for psychiatric survivors. The study is allied with the Community–University Research Alliance (CURA), a Canadian government research grant program administered by the Social Sciences and Humanities Research Council (SSHRC). Participants were stratified based on housing type (housed vs. homeless) and employment status (employed and/or a student vs. unemployed). The sample includes 380 individuals (190 men and 190 women), with a psychiatric diagnosis and/or addiction issue for a minimum of one year. The four-year longitudinal study combines both quantitative (individual structured interview) and qualitative (focus group) data collection methods and preliminary quantitative analysis of the first-year data is underway. Upon its completion, it is hoped that the CURA study will yield results useful for informing policy and practice influencing health and life outcomes for psychiatric survivors and help determine the most effective use of resources to promote social inclusion.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.041 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".