Citizenship and recovery: two intertwined concepts for civic-recovery
Bibliographic record
Abstract
BACKGROUND: Validation of the psychometric properties of a new measure of citizenship was required for a research project in the province of Quebec, Canada. This study was meant to study the interplay between recovery- and citizenship-oriented supportive employment. As recovery and citizenship were expected to be two related concepts, convergent validity between the Citizenship Measure (CM) and the Recovery Assessment Scale (RAS) was tested. METHODS: Study objectives were to: 1) conduct exploratory factor analyses on the CM and confirmatory factor analysis on the RAS tools (construct validity), 2) calculate Cronbach's alphas for each dimension emerging from objective 1 (reliability), and 3) calculate correlations between all dimensions from both tools (convergent validity). Data were collected from 174 individuals with serious mental illness, working in social firms. Serious mental illnesses include major depression, schizophrenia, bipolar disorder, obsessive compulsive disorder, panic disorder, post traumatic stress disorder and borderline personality disorder. RESULTS: Five factors emerged from the exploratory factor analysis of the CM, with good reliability. Confirmatory factor analyses showed that the short and the long versions of the RAS present satisfactory results. Finally, the correlation matrix indicated that all dimensions from both tools are significantly correlated, thus confirming their convergent validity. CONCLUSIONS: This study confirms the validity and reliability of two tools, CM and RAS. These tools can be used in combination to assess citizenship and recovery, both of which may be combined in the new concept of civic-recovery.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".