Nobody listens, nobody wants to hear you: Access to healthcare/social services for women in Canada
Bibliographic record
Abstract
In Canada, an unacceptable number of women live below the poverty threshold. Some subgroups of women, such as Indigenous, visible minorities, immigrants and refugees, older adults, and single mothers are more likely to live in poverty, as they face multiple systemic barriers preventing their financial stability. Further, socioeconomic status, employment, gender, and access to healthcare and social services negatively impact women’s well-being and health. Yet little is known about how these factors affect healthcare behaviours and experiences for women living on a low income. Our goal is to describe and understand how gender and income influence access to healthcare and social services for women living on a low income. Methods: Partnered with a not-for-profit organization, we explored the experiences of women living on a low income in Kingston, Canada. Using participatory, art-based research and hermeneutic phenomenological approaches, our data collection methods included photovoice, semi-structured interviews and culture circles. A purposive sample was recruited. Analysis was conducted following the social determinants of health framework by Loppie-Reading and Wien. Results: Participants perceived the healthcare and social services systems as unnecessarily complex, disrespectful, and dismissive–one where they are mere spectators without voice. They do not feel heard. They also identified problematic issues regarding living conditions, housing, and fresh food. Despite these experiences, participants are resilient and optimistic. Implications: Learning from participants has indicated priority issues and potential, pragmatic solutions to begin incremental improvements. Changing system design to enable self-selection of food items is one example. Conclusion: For an individual to feel others view them as unworthy of care, especially if those ‘others’ are the care providers, is ethically and morally distressing–and it certainly does not invite system-use. While our early findings reveal considerable system improvements are required, we are inspired by and can learn from the strength of the participants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".