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Record W4405138423 · doi:10.52609/jmlph.v5i1.157

Barriers to Occupational Health and Safety Legal Services During Pandemic

2024· article· en· W4405138423 on OpenAlexvenueno aff
Arjun Aryal, A. Shrestha, Yadav Prasad Joshi

Bibliographic record

VenueThe Journal of Medicine Law & Public Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisPublic relationsOccupational safety and healthPsychological interventionQualitative researchBusinessLegal researchMedicinePolitical scienceNursingLawSociology

Abstract

fetched live from OpenAlex

Objectives: This study aimed to identify the barriers to accessing legal services related to occupational health and safety during the COVID-19 pandemic. Methods: The study applied qualitative research methods, including in-depth interviews with 12 practicing lawyers in Nepal regarding their experience with hundreds of clients. The data was analysed using a thematic analysis approach. Results: The study identified key themes that characterise workers' experiences in accessing occupational health and safety (OHS) legal services, as viewed by legal practitioners. These themes included limited knowledge about OHS legal service provision and procedures; perceived high cost of legal services; delay and uncertainty in furnishing justice; intent to protect one's job, oneself, and family; authority of lawyers and health workers; the influence of family members, employer and significant others; hiding OHS problems due to potential stigmatisation, penalisation and threat; and COVID-19 pandemic-associated lockdown and travel restrictions. Conclusions: The study's findings underscore the practical challenges faced by workers in accessing OHS legal services during the pandemic. Despite the legal provisions in the current constitution, acts, and rules, the access of marginalised populations like workers to OHS services is challenged. This highlights the need for specific attention and focused interventions to avail of OHS legal services during the pandemic. The importance of targeted actions in this area cannot be overstated. The findings of this study are significant as they would serve to formulate and execute important policy guidelines to materialise the existing legal provisions on OHS, and will also serve as the basis for further studies.

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)0.024
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.471
Teacher spread0.390 · 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.

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
Published2024
Admission routes1
Has abstractyes

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