Moral Basis for Universal Healthcare Reform: A Utilitarian Approach
Bibliographic record
Abstract
abstract: Universal healthcare has become a regular feature of most developed nations around the world. This characteristic, however, does not extend to the United States, where some 28.2 million Americans remain uninsured or underinsured. In the past few years, the US has been on the precipice of major healthcare overhaul which has brought the debate on government-sponsored coverage to the forefront of political discourse. This thesis explores what it may mean to establish affordable access to healthcare as a right for all Americans. In doing so, it utilizes rule-utilitarian principles to define and assess the moral obligation of the United States' federal and state governments to provide sufficient coverage to all qualifying individuals within the country. This paper focuses on evaluating the current healthcare system in the United States while concentrating particularly on how its fragmented approach limits its success and longevity. It then offers a cross-comparison with the universal healthcare systems of Canada, France, and Japan, nations that outperform the United States in most healthcare measures such as life expectancy, infant and under-5 mortality, medical costs per capita, and disease prevalence. The free-market criticisms of government-provided coverage and its alternative private-insurance-based approach to healthcare in the US are also deliberated. In light of these considerations, this thesis concludes with a commentary on what healthcare reform could look like for the nation as well as examines how a utilitarian appeal to rights likely makes the best case for adopting universal government-sponsored healthcare coverage in the United States.
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 | 0.031 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.064 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".