Breast Cancer among Women Living in Poverty: Better Care in Canada than in the United States
Bibliographic record
Abstract
This historical study estimated the protective effects of a universally accessible, single-payer health care system versus a multi-payer system that leaves many uninsured or underinsured by comparing breast cancer care of women living in high poverty neighborhoods in Ontario or California between 1996 and 2011. Women in Canada experienced better care particularly as compared to women who were inadequately insured in the United States. Women in Canada were diagnosed earlier (rate ratio [RR] = 1.12) and enjoyed better access to breast conserving surgery (RR = 1.48), radiation (RR = 1.60) and hormone therapies (RR = 1.78). Women living in high poverty Canadian neighborhoods even experienced shorter waits for surgery (RR = 0.58) and radiation therapy (RR = 0.44) than did such women in the US. Consequently, women in Canada were much more likely to survive longer. Regression analyses indicated that health insurance could explain most of the better care and better outcomes in Canada. Over this study's 15-year timeframe 31,500 late diagnoses, 94,500 sub-optimum treatment plans and 103,500 early deaths were estimated in high poverty US neighborhoods due to relatively inadequate health insurance coverage. Implications for social work practice, including advocacy for future reforms of US health care are discussed.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".