Waiting Game: Rhetorical Evocations of Canada in U.S. Health Care Debates
Bibliographic record
Abstract
American health policy scholars often use comparisons with Canada to illustrate the benefits and liabilities of certain policy developments, especially concerning single‐payer health care. Few scholars seem to have taken note, however, of the rhetorical work that comparisons with Canada do in American politics. Moving from policy to politics, this article seeks to understand the key rhetorical patterns that characterize evocations of Canada within American health‐care debates. Through an analysis of almost 10 years of American media, the authors argue that five rhetorical frames—waiting, misrepresentation, Canadians traveling to the United States, health outcomes, and the fact that the Canadian system “is not perfect”—comprise the key political dynamics in which rhetoric about Canada plays a role. Ultimately, the authors argue that the evocation of Canada in American health‐care politics creates a policy environment in which nuance and imperfection cannot be acknowledged, thereby forestalling problem solving.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.036 | 0.030 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".