Pursuit of Equity: Women on a Low Income Navigating Access to Health and Social Services in Canada
Bibliographic record
Abstract
BACKGROUND: Existing research highlights the role of social determinants of health, such as education and housing, in predicting health outcomes and the challenges that arise from deficiencies in these areas, often linked to societal inequities. Gender and income are recognized as social determinants of health, yet the complexities of their interplay, particularly for women with low income seeking health and social services in Canada, need more exploration. OBJECTIVE: This study investigates how gender and income intersect to affect access to health and social services for Canadian women with low income. METHODS: Employing a participatory action approach with arts-based and interpretive methodologies, the study partnered with a non-profit organization to engage five women through photovoice, interviews, and a focus group, aiming to capture their experiences in accessing services. RESULTS: The analysis revealed three primary themes: the labyrinth-like complexity of navigating health and social service systems, the importance of mental health sanctuaries, and the value of supportive networks. Participants reported difficulties and frustrations in system navigation, often feeling ignored by service providers. Contrarily, community agencies provided essential non-judgmental support, including daily necessities and emotional care, with the companionship of pets also being a notable source of comfort. CONCLUSION: The findings advocate for a shift towards more person-centred care in health and social service systems to better serve women in vulnerable positions, emphasizing the need to simplify the process of accessing services and ensuring that service providers recognize and address the unique challenges faced by equity-deserving groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".