Gender variations in the relationship between social capital and mental health outcomes among the Indigenous populations of Canada
Bibliographic record
Abstract
BACKGROUND: In this paper we examine the relationship between social capital and two mental health outcomes-self-rated mental health (SRMH) and heavy episodic drinking (HED)-among the Indigenous populations of Canada. We operationalize a unique definition of social capital from Indigenous specific sources that allows for an analysis of the importance of access to Indigenous networks and communities. We also examine gender variations in the relationship between social capital and the two outcomes, as there is a noticeable lack of research examining the influence of gender in the recent literature on the mental health of Indigenous populations in Canada. METHODS: Using data from the 2012 cycle of the Aboriginal Peoples Survey, logistic regression models were estimated to assess if gender was a significant predictor of either SRMH or HED among the entire Indigenous sample. The sample was then stratified by gender and the relationship between two social capital variables-one general and one indigenous-specific-and each mental health outcome was assessed separately among male and female respondents. All analyses were also further stratified into specific Indigenous groups-First Nations, Métis, or Inuit-to account for the unique cultures, histories, and socioeconomic positions of the three populations. RESULTS: Female respondents were more likely to report fair or poor SRMH in the total sample as well as the First Nations and Métis subsamples (OR = 1.48, CI = 1.14-1.91; OR = 1.63, CI = 1.12-2.36; OR = 1.44, CI = 1.01-2.05 respectively). However, female respondents were less likely than males to engage in weekly HED in all three of the same populations (OR = 0.43, CI = 0.35-0.54, all respondents; OR = 0.42, CI = 0.31-0.58, First nations; OR = 0.39, CI = 0.27-0.56, Métis). Social capital from sources specific to Indigenous communities was associated with lower odds of weekly HED, but only among Indigenous men. Meanwhile the strength of family ties was associated with lower odds of reporting fair/poor SRMH among both Indigenous men and women. However, these results vary in strength and significance among the different Indigenous populations of Canada. CONCLUSIONS: The results of this paper address a critical gap in the literature on gender differences in SRMH and HED among the Indigenous populations of Canada, and reveal gendered variations in the relationship between social capital and SRMH and HED. These findings support further investigation into the role that social capital and particularly Indigenous-specific forms of social capital may play as a determinant of health. This research could contribute to future mental health initiatives aimed at strengthening the social capital of Indigenous populations and promoting resilient Indigenous communities with strong social connections.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".