Universalists, Republicans and Rationalists: Exploring Health Sector Solidarity and Its Boundary through the Comparative Experience of Overseas Taiwanese
Bibliographic record
Abstract
Abstract Through users’ cross-system comparative experience engaging with the health systems in Taiwan and other countries, this article probes into their understandings and value judgments and specifically their reasonings for the ‘solidarity with whom?’ question in the health sector solidarity. With the cross-system comparison approach, the study adopted semi-structured interviews with 30 Taiwanese participants who have studied, lived or worked abroad and engaged with the health system in Canada, the USA or the UK. This approach offers the opportunity for one to evaluate the health system in the home country from a relative viewpoint from the host country. The participants suggested that the boundary of Taiwan’s National Health Insurance (NHI) should be as inclusive as possible, covering all legal residents in Taiwan regardless of their status, and that the citizens should share more financial responsibility. The ethical reasons for supporting the NHI include recognizing health sector solidarity among people, considering the coverage as a protection of the human right to health, humanitarian reasons and self-interest. Three archetypes of users emerged from the synthesis: Universalists, Rationalists and Republicans. The cross-system comparative experience makes the participants have more supportive attitudes toward the ideals of health sector solidarity.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.019 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| 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".