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Record W4281647519 · doi:10.1111/ilrs.12244

Retos de seguridad y salud en el trabajo para la gente de mar en actividades esenciales durante la pandemia mundial de COVID‐19

2022· article· es· W4281647519 on OpenAlexaff
Desai Shan

Bibliographic record

VenueRevista Internacional del Trabajo · 2022
Typearticle
Languagees
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsHealth Sciences CentreMemorial University of Newfoundland
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Humanities2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political scienceGeographyArtMedicineVirology

Abstract

fetched live from OpenAlex

Resumen La pandemia de COVID‐19 ha transformado el mundo del trabajo, pero el comercio mundial sigue considerándose una esfera de actividad esencial y el transporte marítimo, como motor de la globalización, no puede detenerse. En este contexto, pocos Gobiernos han permitido a la gente de mar —que transporta más del 90 por ciento de las mercancías mundiales— abandonar sus barcos y regresar a casa. Las restricciones de viaje relacionadas con la COVID‐19 han provocado una crisis de seguridad y salud en el trabajo marítimo. Este artículo, basado en 29 entrevistas, explora los retos de SST que ha afrontado la gente de mar de todo el mundo durante la pandemia.

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)0.005
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0070.012
Scholarly communication0.0060.003
Open science0.0010.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.015
GPT teacher head0.308
Teacher spread0.293 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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