The need to change the narrative, to change the context: Urban indigenous women surviving-or-thriving responses to stressors
Bibliographic record
Abstract
• Indigenous women have varying degrees of control over their life stressors. • A lack of control over built and neighborhood environments was experienced. • Their environments impacted how they managed their mental and physical health. • Drugs and alcohol, shutting down and cutting ties were common survival responses. • Gaining control included engaging in culture, relationship building and advocacy. In Canada, Indigenous women have a range of life stressors and possess a spectrum of behaviours in response to stressors. We aimed to learn more about their life stressors and coping strategies. We recruited women self-identifying as Indigenous living in Toronto, Ontario, to discuss their life stressors through sharing circles and one-on-one interviews. A thematic analysis was conducted on the transcribed semi-structured discussions. Our data shows the participants’ experiences of control over stressors ranging from loss of control, being controlled, and attempting to control their socio-economic situations and financial constraints, their perceived identities and images as well as the impact of the social environment on their health and wellbeing. We also summarized how they address stressors and their experiences with and understandings of how the concept or practice of control manifests in their responses. Our findings provide a glimpse into the complexities of coping and the sense of control Indigenous women have over life stressors and has important implications for service providers, policy-makers and researchers.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.016 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".