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Universal Health Care is a Bad Thing

2008· article· en· W2330918246 on OpenAlexaboutno aff
Kenneth J. Wright

Bibliographic record

VenueEmergency Medicine News · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsNothingHealth careMedicineEmergency departmentMedical emergencyBusinessLawNursingPolitical science

Abstract

fetched live from OpenAlex

Editor: In his editorial (EMN 2008;30[4]:4), Dr. Lewis Goldfrank suggests that the following theoretical question should be included in the emergency medicine board examination: Universal health care is (A.) a good thing or (B.) a bad thing. Dr. Goldfrank's answer to that question would have been A. He would have gotten that answer wrong. Dr. Goldfrank and I have vastly different perspectives on the concept and reality of universal health care. I did my emergency medicine training in Canada in the mid-1970s. I saw firsthand the disaster called universal health care. Tax dollars were paid into a general fund from which health care dollars were dispensed. When money became tight, bureaucrats rationed care. At that time, little could be done for stroke patients when bureaucrats decided that no beds would be allotted for those patients. As an emergency resident at that time, I was forced to send newly hemiplegic patients home with only family members to care for them. Women waited months for a biopsy of suspicious breast lesions. Physicians fled from this system into the U.S. This system cost a lot of money, and hurt a lot of patients and their families. The 47 million so-called uninsured people in the U.S. include a large number of young healthy folks who, understandably, choose to spend their money on things other than health insurance. Because we have hospitals that turn a blind eye to theft of service, they get away with paying little or nothing for emergency care when they finally do become sick or injured. If someone walked out of a store with a TV set and didn't pay for it, he would end up in jail. The truly needy should continue to be cared for at society's expense, but a man with $2000 worth of tattoos and piercings on his body who smokes $3000 worth of tobacco and drinks $1000 worth of alcohol yearly will have a very hard time convincing me that someone else should pay for his health care. He has chosen to spend $4000 a year on tobacco and alcohol rather than on health care. Every day a patient with rotten teeth tells me that he “can't” go to a dentist because he has no insurance. If a tire blows out on his car, though, he doesn't delay replacing it because he doesn't have insurance. He opens his wallet and pays for the tire. If he saved the $10 a day he spends on tobacco, soon he would be able to pay cash for dental service just like he paid for the tire. The last two things we need in this country are another group of dependent, entitled people and the government running a universal health care system. The answer to the board question is B. Government-sponsored universal health care is a bad thing. Kenneth J. Wright, MD Redding, CT

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.052
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0050.006
Scholarly communication0.0140.010
Open science0.0050.003
Research integrity0.0250.046
Insufficient payload (model declined to judge)0.0210.013

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.

Opus teacher head0.099
GPT teacher head0.322
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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