Expanding Notions of Culture and Ethics in Health and Medicine to Include Marginalized Groups: A Critical Perspective
Bibliographic record
Abstract
I am concerned with the manner in which an almost exclusive focus on the individual has been part of a more general process that increasingly marginalizes the most vulner able people. A highly individual view of what constitutes the realm of ethics stems both from the cultural value of extreme individualism expressed in the industrialized west and a narrow conceptualization of culture itself. I will argue that this has pro found consequences not just for groups like minorities and the poor, but also ultimately for our species itself. This is because a failure to attach ethical discussions to groups cannot adequately critique ecological disasters. Ultimately, it is our species that is threatened by a medical ethics narrowly bound to the notion of individual rights rather than to ideas of responsibility and human rights. I will illustrate this with examples drawn from the evolution of increasingly virulent diseases created largely by the pharmaceutical industry and the obsessive quest for individual longevity via organ transplantation that has led to a profound misunderstanding of cancer.
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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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.014 | 0.103 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 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".