El riesgo emergente que constituyen las agresiones y violencia que sufren los médicos en el ejercicio de su profesión: el caso de España
Bibliographic record
Abstract
The article presents some considerations on the aggressions within the area of Health Professionals, considering those facts as an international phenomenon which is latent in European countries (Spain, France, Great Britain) as well as in other parts of the world (Latin America, United States, Canada, Australia, New Zealand). In Spain, the studies carried out with medical staff demonstrate that the aggression rate is approximately of 0,2/100.000 medical acts. The objective of this article is to place emphasis on the aggressions and violence suffered by the medical staff in the course of their duties, and since it is a relatively new phenomenon there is not much data on the topic. For this reason I consider important to deepen, investigate and outline possible causes to this serious problem which according to the World Health Organization (WHO) denounces that almost 25 percent of all the incidents of violence at work take place in the health sector.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".