Health Care Reform and the Paradox of Efficiency: “Writing in” Culture
Bibliographic record
Abstract
Widespread global migration is occurring at the same time that health care delivery systems in Western nations are undergoing major restructuring. The call for health care to be more efficient, economical, and responsive to diverse cultural populations has come from several sectors, including governments and researchers. This has led to policies to address perceived deficiencies in health care services. The authors draw on their research at health care institutions in a western Canadian city to probe, first, how the concept of culture is interpreted within organizations; and second, how culture is "written into health systems" as they undergo restructuring. Meanings and interpretations of culture are not transparent; moreover, "writing in" culture is not simply a matter of health care providers learning about their clients' "belief systems" and being sensitive to these beliefs. Belief systems and people's experiences of the care they receive are negotiated within highly complex "organizational cultures," located in broader macroeconomic and political structures, and discourses that shape how health care systems are organized. The authors consider whether current discourses on cost containment are in competition with providing equitable health care services to diverse client populations.
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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 | 0.033 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.089 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.009 |
| 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".