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Record W2708231924 · doi:10.1504/ijmp.2017.10005857

Construction site safety in small construction companies in Saudi Arabia

2017· article· en· W2708231924 on OpenAlexaff
Murat Şakir Eroğul, Mohsen Mania Alyami

Bibliographic record

VenueInternational Journal of Management Practice · 2017
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsOccupational safety and healthBusinessConstruction site safetyConstruction industryEffective safety trainingPerceptionSafety cultureOperations managementTransport engineeringEngineeringEnvironmental healthConstruction engineeringManagementPublic healthPsychologyMedicineHealth policyNursingOccupational health nursing

Abstract

fetched live from OpenAlex

Construction site safety concerns in small construction projects in Saudi Arabia are alarming due to the large number of accidents per year. The purpose of this research is to explore construction worker's perceptions regarding construction site safety climate. An integrative model of workplace safety has been utilised to design and administer a questionnaire to workers in five small residential construction sites in the city of Najran. The results demonstrate a lack of adherence to occupational health and safety regulations by employers, a need for construction site safety protocols and enhanced external inspection systems, an unawareness among participants in regards to the safety measures endorsed by their companies, and indications of leniency due to favouritism by external inspectors. In conclusion, the study contributes to construction science and practice by identifying factors contributing to construction worker perception of safety which may help employers enhance the safety climate of small construction sites.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.085
GPT teacher head0.477
Teacher spread0.392 · 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 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

Citations6
Published2017
Admission routes1
Has abstractyes

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