Propuesta para protocolizar el abordaje de daños emocionales en investigación con seres humanos
Bibliographic record
Abstract
Artículo teórico-reflexivo que responde al objetivo de generar lineamientos para el abordaje de daños en el ámbito emocional en investigaciones con seres humanos. Utilizando directrices de la Organización Mundial de la Salud, de la Asociación Profesional de Enfermeras de Ontario y, como referente, a la teorista Joyce Travelbee, se genera un diagrama de flujo como propuesta para protocolizar el abordaje de daños emocionales en investigación con seres humanos, con base en la formalidad, la rigurosidad y la empatía que requiere el proceso de ayuda ante potenciales daños generados en una investigación. Esto debido a que resulta perentorio presentar guías predefinidas en cualquier investigación que, tras un minucioso análisis, presente el riesgo de compromiso emocional en los participantes.
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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 | 0.422 | 0.414 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".