Barriers to and facilitators of community participation among Latinx migrants with disabilities in the United States and Latinx migrant workers in Canada: An ecological analysis
Bibliographic record
Abstract
Individuals migrate to improve their wellbeing and quality of life, and often experience adverse situations, both during the process of migration and once within the host country. The purpose of this paper is to unpack the barriers to and facilitators of community participation, among Latinx immigrants with disabilities in the United States and Latinx migrant workers in Canada, following the Social Ecological Model. The authors draw from an appraisal of existing literature and their own participatory research with Latinx immigrants. Based on this integrative literature review, Latinx experience individual issues such as language barriers and lack of knowledge of the services available to them. At the community level they experience discrimination, limited opportunities for community participation, and lack of opportunities for meaningful employment. At the systemic and policy level in the United States, the antimigrant political environment keeps Latinx immigrants with disabilities from participating in their communities due to fear of deportation. In Canada, Latinx workers experience the paradox of migration and discrimination. The discussion of barriers and facilitators is followed by recommendations for community research and action.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".