Exploring the Mental Health Benefits of Physical Activity for Immigrant, Refugee, and Undocumented Women: Through an Intergenerational Lens
Bibliographic record
Abstract
A robust body of research highlights that refugee women encounter heightened risks of experiencing life-threatening events and trauma due to diverse systemic and structural barriers, leading to mental health instability.Limited access to mental health resources exacerbates these challenges for immigrant, refugee, and undocumented (IRU) women, particularly in high-income resettlement countries.Although physical activity (PA) interventions show promise in supporting the promotion of positive mental health in IRU women, barriers to access remain.Despite the pressing need for accessible PA programming, there is a lack of literature on best practice for developing suitable interventions for IRU women.Through an intersectional lens, this study leverages a community-based participatory action approach to investigate the experiences and perceptions of current PA among IRU women.Additionally, the study will explore intergenerational perceptions between first and second-generation IRU women to understand mental health concerns and barriers to PA.Through focus group discussions and semi-structured interviews, this research seeks to inform the development of appropriate and trauma-informed PA programming for this population.
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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 | 0.003 | 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 | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".