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Record W4327919546 · doi:10.1016/j.shaw.2023.03.007

Scoping Review of the Occupational Health and Safety Governance in Sudan: The Story So Far

2023· article· en· W4327919546 on OpenAlexaff
Rasha Abdelrahim, Victor Olabode Otitolaiye, Faris Omer, Zeena Abdelbasit

Bibliographic record

VenueSafety and Health at Work · 2023
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCorporate governanceLegislationEnforcementScope (computer science)Government (linguistics)Occupational safety and healthPublic relationsBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Background: The reoccurrence of occupational accidents in Sudan is evidence of a lack of effective Occupational Health and Safety (OSH) governance in Sudan. Methods: This scope review research articles on OSH governance in Sudan from different sources, including international websites, official government websites, original research articles in journals, and various reports. The five stages of the scoping review followed in this study are: identifying the research question; identifying relevant studies; study selection; charting the data; collating, summarizing, and reporting the results. Results: There is numerous legislation in place; however, there is no evidence of their enforcement, and no formal bodies at the national level are identified as being responsible for their enforcement. Conclusion: Having multiple authorities with overlapping responsibilities hinders OSH governance. An integrated governance model is proposed to eliminate overlapping duties and to facilitate the participation of all stakeholders in the governance process.

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)0.027
metaresearch head score (Gemma)0.084
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.084
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0160.025
Science and technology studies0.0030.003
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0040.003
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 head0.116
GPT teacher head0.484
Teacher spread0.368 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2023
Admission routes1
Has abstractyes

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