Bibliographic record
Abstract
What are the final limits of medicine? What should we not try to cure medically, even if we had the necessary financial resources and technology? This book philosophically addresses these questions by examining two mirror-image debates in tandem. Members of certain groups, who are deemed by traditional standards to have a medical condition, such as deafness, obesity, or anorexia, argue that they have created their own cultures and ways of life. Curing their conditions would be a form of genocide. Members of other groups are seeking to provide medical treatment to what would conventionally be deemed 'cultural conditions'. Mild neurotics who take anti-depressants to elevate their mood, runners who use steroids, or men and women seeking cosmetic surgery are asking for medical treatment for problems that might be solved culturally, by changing norms, pressures, or expectations in the broader culture. Each of these two debates endeavors to locate medicine's final frontier and to articulate what it is that we should not treat medically even if we could. This volume analyzes what these two contemporary debates have to say to each other and thus offers a new way of determining medicine's final limits.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.050 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".