MétaCan
Menu
← Back to cohort
Record W6990321775

Developing a maturity model and metrics to evaluate the occupational health and safety performance of sustainable building projects in the Manitoba construction industry

2021· dissertation· en· W6990321775 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2021
Typedissertation
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
FundersCenter for Construction Research and Training
KeywordsMaturity (psychological)SustainabilityCapability Maturity ModelMetric (unit)Occupational safety and healthConstruction industry
DOInot available

Abstract

fetched live from OpenAlex

Despite recent efforts aimed at promoting sustainability, very little has been done to integrate health and safety into the sustainability evaluation of the built environment. This has made sustainable building projects more prone to incidents than non-sustainable ones. The goal of this research was to evaluate the health and safety performance of sustainable building projects in Manitoba. This research involved developing and validating a Sustainable Health and Safety Maturity Model consisting of 251 critical to safety practices organized into 22 safety maturity drivers. The maturity model was implemented on 20 sustainable building projects and 21 non-sustainable ones using a questionnaire survey. The research also developed 34 performance metrics following a detailed literature review and validated them by expert judgment before implemented them on seven sustainable building projects and seven non-sustainable ones. The maturity model results were correlated to performance metric results to investigate the relationship between maturity and performance. Findings from the research confirmed the validity of the 22 safety maturity drivers of the maturity model and 25 of the 34 metrics. The results showed that sustainable building projects had a slightly higher health and safety maturity than non-sustainable ones; however, the difference was statistically insignificant. Larger-sized companies had more mature health and safety practices compared to small sized companies. The most mature safety maturity drivers were “safety policy and standard implementation” and “safety inspections” while the least mature were “project team selection” and “alcohol and drug testing”. The research found that sustainable buildings had higher incident rates by 12.7% than non-sustainable one; however, the difference was statistically insignificant. Also, a project’s health and safety maturity was strongly correlated to its incident rates. The percentage of workers with unsafe behaviour based on conducted safety observations was strongly correlated with the percentage of workers who attended safety meetings. This research is the first in Canada to evaluate the health and safety maturity and performance of sustainable building projects. The research contributes to the existing body of knowledge in the field which can be translated to evidence-based guidance for stakeholders in the construction industry in order to make for safer sustainable buildings.

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)0.016
metaresearch head score (Gemma)0.021
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: Methods · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.005
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
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 head0.087
GPT teacher head0.388
Teacher spread0.301 · 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
GenreMethods

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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueMspace (University of Manitoba)→Same topicOccupational Health and Safety Research→French-language works237,207→