Inclusion of Indigenous workers in workplace mental health
Bibliographic record
Abstract
Purpose This paper highlights inclusion issues Indigenous people experience maintaining their mental health in the workplace. Design/methodology/approach Using a grounded theoretical approach, five sharing circles were conducted with the Nokiiwin Tribal Council's community members to better understand inclusivity issues related to workplace mental health. Findings Five themes emerged from the data related to enhancing inclusivity and workplace mental health for Indigenous workers: (1) connecting with individuals who understand and respect Indigenous culture; (2) respecting Indigenous traditions; (3) hearing about positive experiences; (4) developing trusting relationships and (5) exclusion is beyond the workplace. Research limitations/implications The next step is to finalize development of the Wiiji app and evaluate the effectiveness of the app in helping Indigenous workers feel included at work and to improve workplace mental health. If effective, the Indigenous-developed e-mental health app will be promoted and its benefits for helping Indigenous workers feel included at work and also for providing accessible mental health resources, will be known. In the future, other Indigenous groups may be potentially interested in adopting a similar application in their workplace(s). Originality/value There is very little known about inclusivity issues related to Indigenous workers' maintaining their mental health. This paper identifies major issues influencing the exclusion and inclusion of Indigenous workers.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.021 |
| Research integrity | 0.000 | 0.000 |
| 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".