An ID card allowing access to municipal services for migrants with precarious status in Montreal and its influence on social inclusion: a mixed method study
Bibliographic record
Abstract
Purpose An identification card facilitates access to municipal services for migrants with precarious status (MPS) in Montreal. The purpose of this study was to explore from MPS’ perspective the utility of the identity (ID) card and its influence on social inclusion for MPS. Design/methodology/approach A sequential explanatory mixed methods design was used. First, a descriptive phone survey was administered (n = 119). Associations between ID card use and levels of social inclusion were assessed using ordinal logistic regression. Second, semi-structured interviews (n = 12) were done with purposely selected participants. Results were mixed using a statistics-by-theme approach. Findings Results showed that ID card users compared to nonusers reported higher levels of participation in society and more control/independence in daily life. No statistical associations were found between card use and sense of belonging nor sense of safety. Interviews highlighted that the ID card enabled participation in socio-recreational activities and perceived empowerment. A heightened sense of belonging was also found. Interview participants expressed fear of police despite owning the ID card. Practical implications Overall, although the municipal ID card promoted social inclusion for MPS, there is a need to render the ID card official to fully achieve this goal. Findings can inform the creation of public policies that foster inclusion and health of MPS in cities around the world. Originality/value Evaluation from MPS’ perspectives of the first ID card program of its kind 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".