Author's Reply to a Letter to the Editor: “Doctors and Patients Working Together”
Bibliographic record
Abstract
To the Editor, I am pleased to know that Mr. Fowler[1] and his family are in good health as a result of receiving good care in Canada. I am moved by his story, but not persuaded. Anecdotal evidence is not a sound basis for public policy decisions any more than it is for medical decisions. The facts that argue against a single-payer system are not clinical, but economic. Mr. Fowler notes that he benefited from MRI technology, one of many American healthcare innovations that are fruits of America's market-based system. Were America to join with the rest of the world, our engine of innovation would be stifled, depriving the entire world of the free ride that it has taken at our expense and collapsing the entire house of cards. Mr. Fowler claims that his taxes are comparable to those in the United States, again based on an anecdotal comparison with a friend in California. The fact is that, according to the Organization for Economic Cooperation and Development (OECD), average Canadians pay 50% higher national and subnational tax rates than their US counterparts. (Please click the link for more information.) Canadians and those in other Western nations are fortunate to have benefited from America's defense shield and the innovations of our market-driven healthcare system. Even so, around the world, socialized systems, collapsing from the weight of the unsustainable economic contradictions of their systems, are desperately trying to return to the discipline of the market. In the United Kingdom, labor has introduced market-based reforms. In Germany, the recent election was a drama of trying to wean the populace from the soothing benefits of socialism. The course of history is clear. Communism and socialism have crumbled and capitalism has prevailed, because it alone recognizes and respects the realities of human nature. Despite these facts, socialist sirens continue to try to lure us toward its rocky shoals, trying to persuade us to burden the taxpayer with billions of dollars of healthcare expense now borne by the private sector. Hopefully, we will have the will to stay true to the principles that have made this nation great – economic and political freedom – as we continue to perfect our system. Readers are encouraged to respond to George Lundberg, MD, Editor of MedGenMed, for the editor's eye only or for possible publication via email: ten.epacsdem@grebdnulg.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".