Medición funcional en el dominio de la ética empírica
Bibliographic record
Abstract
El presente artículo propone un enfoque empírico de la ética derivado de la teoría psicológica del juicio humano propuesta por Norman Anderson. Muestra cómo la metodología de esta teoría —denominada medición funcional— puede utilizarse para caracterizar las diversas posiciones personales que existen en todas las sociedades respecto a los problemas de salud pública. Los principales resultados de tres estudios realizados en tres países diferentes (Guinea, Francia y Colombia) se presentan como ilustración de lo que puede aportar este enfoque. Dichos análisis se centraron en tres problemas deliberadamente muy diferentes: (a) el deber de atender a los pacientes infectados, en caso de una epidemia que ponga en peligro la vida de los cuidadores; (b) la aceptabilidad de la reproducción postmortem, en el caso de los soldados que mueren en combate, y (c) la aceptabilidad del suicidio asistido por un médico.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.040 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".