Health care provider obligations in caring for patients with tuberculosis
Bibliographic record
Abstract
It is well acknowledged that physicians and other health care providers have an obligation to provide clinical care to their patients even under occasionally difficult circumstances. However, the exact degree and extent of that obligation, and the various scenarios under which it might be lessened or even cease to exist, have recently become the focus of much discussion and debate. The reason for this emerging debate is twofold: the recent occurrence of pandemic viruses such as severe acute respiratory syndrome and H1N1, and the emergence of highly resistant strains of infectious pathogens such as multi and extensively drug-resistant tuberculosis (TB). Health care providers have been asked to place themselves at risk to an extent many did not foresee when they chose to enter their profession, and many have done so under difficult conditions, often without adequate supplies and support. The present article explores the ethical obligations as well as the reciprocal rights of health care providers who are caring for patients with TB, with a particular focus on drug-resistant strains of the bacterium. It is a condensed version of a World Health Organization (WHO) Working Paper prepared for the WHO Working Group on Ethics and Tuberculosis.
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 | 0.024 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".