Bibliographic record
Abstract
Safety culture is a critical aspect of ensuring safe and productive construction sites.However, many studies in the field of construction that focus on safety culture overlook the unique attributes of construction environments.Current models for safety culture in construction fail to fully encompass the dynamic and diverse nature of construction sites where individuals with differing backgrounds, professions, and levels of experience collaborate to complete projects.These individuals not only come from different cultures and speak different languages, but they also have various psychological, behavioral, and knowledge traits that can affect their safety practices and behaviors.Moreover, different organizations have different settings and perceptions about the safety of their workers and workplace, which can further complicate the development of effective safety cultures in construction.Therefore, there is a clear need for research that focuses on developing more context-specific models for safety culture in construction that can account for these unique attributes and complexities (Hallowell et al., 2016; Hinze and Tracey, 2016; Lingard et al., 2018).The present study presents a framework that incorporates multiple facets of safety culture, including psychological factors, organizational factors, knowledge and awareness, behavioral factors, safe working conditions, safety-oriented climate, resilience, and unsafe behaviors.The proposed framework captures the relationship between these variables and the safety culture of the construction industry in Nepal.The results inferred from the analysis of the survey showed that among the eight variables included in the study (psychological dimension, organizational dimension, knowledge dimension, behavioral dimension, safe workplace, safety climate, resilience, and unsafe behavior), seven of them (excluding unsafe behavior) had a direct positive impact on safety culture in the construction industry of Nepal.In other words, these seven variables were found to be positively associated with the development of a strong safety culture in the construction industry of Nepal.On the other hand, unsafe behavior was found to have a negative impact on safety culture, implying that if workers engage in unsafe behavior, it can undermine the development of a positive safety culture in the workplace.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".