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Record W1725136507

Health and safety in the workplace - conclusions

2015· article· en· W1725136507 on OpenAlexaboutno aff
Manuel Luque Parra, Anna Ginès i Fabrellas

Bibliographic record

VenueIuslabor · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety in Workplaces
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceCartographyGeographyArt
DOInot available

Abstract

fetched live from OpenAlex

The Comparative Labor Law Dossier (CLLD) in this issue 2/2015 of IUSLabor is dedicated to Health and Safety in the Workplace. Aside from Spain, we have had the collaboration of internationally renowned academics and professionals of the following countries: Belgium, France, Italy, Luxembourg, the United Kingdom, Chile, Costa Rica, Mexico, Peru, Uruguay, Canada and the United States. Without detriment to recommend our readers the reading of these articles, we have drawn the top 10 conclusions. Furthermore, we have elaborated a summary table with the most relevant issues regarding health and safety in the workplace in the different legal systems analyzed in this issue of IUSLabor. El Comparative Labor Law Dossier (CLLD) de este numero 1/2015 de IUSLabor esta dedicado a la sucesion y transmision de empresas. Ademas de Espana, hemos obtenido la participacion de academicos y profesionales de prestigio de los siguientes paises: Belgica, Francia, Italia, Luxemburgo, Reino Unido, Chile, Costa Rica, Mexico, Peru, Uruguay, Canada y Estados Unidos. Sin perjuicio de recomendar a nuestros lectores la lectura del capitulo correspondiente a cada uno de los paises citados, en las paginas que se suceden hemos incluido las 10 conclusiones principales que hemos alcanzado. Asimismo, hemos elaborado un cuadroresumen con aquellas cuestiones mas relevantes en materia de seguridad y salud laboral en los distintos ordenamientos juridicos analizados en este numero de IUSLabor. Titulo: Seguridad y salud laboral. Conclusiones IUSLabor 2/2015 Manuel Luque Parra and Anna Gines i Fabrellas 2

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.456
Teacher spread0.378 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2015
Admission routes1
Has abstractyes

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