Bibliographic record
Abstract
Climate change can have many devastating effects on health and disrupt occupations, including activities of work, self-care, and leisure. Thus, occupational therapists (OTs) have a role to play in climate action by promoting sustainable occupational therapy practices and educating clients on the importance of employing more eco-responsible occupations. However, within the Canadian context, the OTs who support climate action may face many difficulties when advocating for it. This analytical essay will explore the multiple barriers to the implementation of sustainable practices in Canada that OTs encounter. As most Canadian citizens adopt consumerist lifestyles due to Western ideals and systems, this can affect clients’ and professionals’ receptibility to sustainability education and motivation. Moreover, many Canadian OTs lack education on climate action in their profession, and current resources are either overwhelming or unclear. Nonetheless, Canadian OT leadership, specifically the CAOT, has begun taking initiative, thus while work is still in progress, the outcomes have yet to appear, however there are great hopes for the future. In conclusion, while there are still many barriers to overcome, OTs have a great potential to become active change agents in the fight against climate change by collaborating with clients and colleagues alike to spread awareness and build sustainability in occupations.
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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 | 0.016 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".