What prosperous, highly educated Americans living in Canada think of the Canadian and US health care systems.
Bibliographic record
Abstract
BACKGROUND: There are no reported head-to-head comparative assessments of health care in any two countries by people who have experienced both. We sought to report the experiences and views of Americans living in Canada who have used both health care systems as adults. METHODS: We surveyed a sample of Americans living in Canada. We used 5 communication strategies to obtain the sample and asked respondents to provide experience-based ratings of various dimensions of health system quality. RESULTS: The survey was completed by 310 people who met the inclusion criteria. This group was highly educated (58% with a master's degree or higher) and prosperous (51% of households had a yearly income > $100,000). Seventy-four percent rated the overall quality of US health care as excellent or good, compared with 50% who gave this rating to Canadian health care. Most preferred the American system for emergency, specialist, hospital and diagnostic services. Respondents rated the Canadian system more highly for access to drug therapy and expressed similar views of the two systems with respect to care from a family physician. The features of the US system rated most positively were timeliness and quality; those rated most highly in the Canadian system were equity and cost-efficiency. The most negatively viewed features of the US system were cost/inefficiency and inequity; those of the Canadian system were wait times and personnel shortages. Although respondents generally rated the components of the US system more favourably than Canada's, when asked which system they preferred overall, 45% chose the US system and 40% chose Canada's. CONCLUSION: Americans living in Canada generally rated the US health care system as being better than the Canadian system. However, they acknowledged the inefficiency and inequity of the US system, and nearly half preferred the Canadian system despite its perceived problems.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".