Building Diverse, Equitable, and Inclusive Organizational Culture to Support Worker Mental Health and Wellbeing: A Qualitative Study of Employer and Worker Perspectives in Ontario Construction Skilled Trades
Bibliographic record
Abstract
This study explored Ontario construction skilled trades employer and worker perspectives on workplace diversity, equity, and inclusion (DEI) and the promotion of worker mental health and wellbeing through building DEI organizational culture. A phenomenological qualitative study was conducted. Fifty-two ( N = 52) participants were recruited and interviewed. Interview data were analyzed using a six-step thematic approach. Three themes were developed: 1) Challenges in organizational culture : participants reported that sexism and biased beliefs on the professional competency of workers from under-represented groups were prevalent within their organizations. Participants highlighted business leadership’ s role in building DEI organizational culture and addressing issues that have affected their organizational reputations and worker retention. 2) Barriers to promoting DEI : a meritocratic hiring approach was identified and restricted the opportunities for under-represented groups. Participants identified a lack of accommodations available in their workplace environment, and some reported lacking awareness of DEI-related issues. 3) Strategies to promote DEI : participants suggested that increasing early career opportunities could help apprentices from under-represented groups build experience and make informed career decisions. These opportunities may also help employers understand an apprentice’s qualifications. Establishing various resources and peer support systems to support the mental health and wellbeing of under-represented workers was also suggested. Multiple challenges existed within the current skilled trades organizational culture, including sexism, biases, hiring barriers, and insufficient accommodations and awareness. Creating career opportunities and social support systems is needed to address these challenges and support worker mental health and wellbeing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".