The need for education about death in medical practice
Bibliographic record
Abstract
Colombia is one of the leading countries in the world regarding regulations and rights at the end of life. Currently, legislation on access to palliative care, limitation of therapeutic effort, euthanasia, euthanasia in children and adolescents, conscientious objection for doctors, and medically assisted suicide is decriminalized. Meanwhile, the remaining Latin American countries are just beginning the discussion about dignified death. Among many reasons for this delay, one of them is that it begins with the most controversial of issues, euthanasia, instead of focusing on humanizing the end of life. Although, etymologically, euthanasia means "good death," a good death does not mean euthanasia. The definition of a good death is complicated because it corresponds to an individual notion affected by culture, religion, society, and medical science. Due to the lack of definition, the tools available to estimate the quality of death and end-of-life care are still unreliable. One of the most recognized criteria to define a good death is the preference of the place to die of the patient, but this depends on factors of the individual, their family environment, the disease, the logistical possibilities of the health system, and the health team that accompanies the process. Some of these determinants can be modified, but not others. Health team care is the one with the greatest potential and, possibly, requires the most investment in education and organization. For physicians, death is transforming from being a natural part of the human experience into a crisis of patient health from which they must be rescued. In addition, technology-based clinical training ensures that they are well qualified to prolong life and poorly prepared to confront death or discuss it with their patients. The problem is bigger than it seems because the conviction about reliance on hospital-based, technologized medicine at the end of life is applicable to them. Research in Canada found that physicians died more in intensive care units and used more palliative care than the general population, but there was no difference in the possibility of dying at home.
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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 | 0.003 | 0.105 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".