La salud y la seguridad de los alumnos en centros de capacitación profesional: enfoques, representaciones y género
Bibliographic record
Abstract
RESUMENEl objetivo de esta investigación ha sido estudiar las problemáticas de la salud y seguridad en el trabajo (SST), y entre ellas la de los alumnos, en centros de formación profesional.Se han empleado diversos métodos con 76 participantes (dirección, profesionales, docentes, alumnos): entrevistas individuales y colectivas, cuestionarios auto administrados, observaciones, análisis de materiales educativos sobre SST.Estos han permitido estudiar las experiencias de SST, las prescripciones, los enfoques, los roles y los factores que influencian las representaciones y el aprendizaje.Los alumnos (20) provenían principalmente de las formaciones en Peluquería y en Electromecánica de sistemas automatizados (19).Los resultados revelan que los distintos grupos de actores tienen representaciones diferentes, que los alumnos están más preocupados por su SST de lo que creen sus capacitadores, cuáles son los daños a la salud que se producen, y que estos ocurren con mayor frecuencia en los alumnos de Peluquería, y cuáles son las perspectivas de género en SST.La discusión abarca el enfoque y los métodos de investigación, los enfoques en SST, las intervenciones que se desprenden de esta investigación y los aspectos a desarrollar. RESUMO A SAÚDE E A SEGURANÇA DOS ESTUDANTES NUM CENTRO DE FORMAÇÃO PROFISSIONAL: ABORDAGENS, REPRESENTAÇÕES E GÉNERO.O reconhecimento das doenças profissionais é um fator importante na promoção da prevenção nos locais de trabalho.Este reconhecimento foi instituído na Bélgica em 1927.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".