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Record W2104494948 · doi:10.5539/ibr.v6n8p68

Construction Safety Management Climate in Kolkata, India

2013· article· en· W2104494948 on OpenAlexvenueno aff
Himadri Guha, Biswajit Thakur, Partha Pratim Biswas

Bibliographic record

VenueInternational Business Research · 2013
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsSafety cultureHofstede's cultural dimensions theoryBusinessPerceptionSafety climateOccupational safety and healthMarketingPsychologyManagementSocial psychologyMedicine

Abstract

fetched live from OpenAlex

A literature survey has revealed that workers in construction sites are subjected to hazardous conditions all over the world and more so in developing countries. Kolkata, India is no exception. Three surveys namely workers’ safety perceptions, managers’ safety practices and cultural attitudes towards safety for both the workers and the managers have been conducted in four construction sites in and around Kolkata. The responses have been studied with statistical techniques like factor analysis, correlations and multiple regressions. The cultural dimensions were based on Hofstede (1991). It has been found that the awareness and belief of the workers have no significant correlations with the cultural dimensions. The workers have no safety related cultural ties and would be logical in accepting safety prescriptions. It has been further noted that workers’ sensitivity to safety awareness is positively correlated with operational practices of managers. Therefore, enhanced safety training to managers which is comparatively easier would increase safety awareness among the managers which in turn would increase the safety awareness to workers.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.103
GPT teacher head0.510
Teacher spread0.407 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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