Challenges in accessing health care services : Canadian children living in mixed-status families
Bibliographic record
Abstract
Few studies have explored the prevalence of Canadian children with family members that have precarious legal status and the impact of parental immigration status on a child's access to health care in Canada. This quantitative research study uses a rights-based approach to discuss secondary data collected retrospectively between 2005-2009 at a medical clinic for uninsured patients in eastern Toronto, Ontario (n=128). Demographic, immigration, and health-related factors are presented, and parental immigration status and health-seeking behaviours are explored. Findings indicate that: many Canadian children (Canadian-born and naturalized Canadians) are uninsured; Canadian children who attend the clinic are sick, as opposed to accessing well-child check-ups; and, a group of Canadian children living in mixed-status families are accessing health care facilities for medically uninsured patients. This study highlights mixed-status families, and the potential impact on children's access to health care. This study helps fill the research gap regarding uninsured Canadian children. It is intended to increase community and professional awareness about impingements made in fulfilling Canadian children's right to access the "universal" health care services they have been promised. In turn, this research could inform future policy, practice, and research within health care, educational, and governmental domains.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".