Bibliographic record
Abstract
[Abstract] In America today, many go without proper healthcare treatment due to rising healthcare costs. In this essay, I argue that corporate America and the politicians they own are not only igniting rising healthcare costs but are also reaping the benefits, at the literal expense of American lives. In today’s political realm, the topic of healthcare comes up often with different perspectives. However, oftentimes a whole story is not told with regards to cost, who’s affected, and solutions that could be used to work on solving this crisis in America. In this paper, I argue that the costs of healthcare are too high due to administrative costs, costs of pharmaceuticals, and the corruption that exists on the federal level which allows both of these issues to plague America. In order to remedy these issues, I argue for a single-payer healthcare system. This system would work to decrease healthcare costs, provide coverage for more Americans, and save the American Government money in the long-run. While most critique this idea to solve the health crisis in America, stating it will be too expensive and offer little change. However, these have been unfounded in both studies and cases that have single-payer systems around the world. In this essay, I often reference Canada not only due to their close proximity but because they used to face these same healthcare issues America faced in the 1960’s. This paper hopes to better explain the rising costs of healthcare, how they affect Americans, and why it is so important we deal with the issue before costs become too high.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| 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".