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Record W1927277816

El riesgo emergente que constituyen las agresiones y violencia que sufren los médicos en el ejercicio de su profesión: el caso de España

2010· article· es· W1927277816 on OpenAlexaboutno aff
María de las Mercedes Martínez León

Bibliographic record

VenueRevista Bioética · 2010
Typearticle
Languagees
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsnot available
Fundersnot available
KeywordsPhenomenonLatin AmericansHumanitiesPolitical scienceHealth professionalsWork (physics)Health careLawArtPhilosophyEngineering
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.336
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2010
Admission routes1
Has abstractyes

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