Achieving a caregiver-friendly workplace standard for Canadian carer-workers: An ex ante evaluation of potential uptake
Bibliographic record
Abstract
With the assistance of a Committee of experts, McMaster University partnered with the Canadian Standards Association (CSA) to develop the Caregiver Inclusive and Accommodating Organizations Standard (B701-17) . The Standard provides workplace guidelines to better accommodate carer-workers through building carer-friendly workplace programs. A qualitative ex ante evaluation was undertaken to determine stakeholders’ (n=17) views regarding the significance and potential uptake of the Standard . This involved seeking feedback from stakeholders in various types of organizations across Canada, after they had read the draft Standard . Following transcription, interviews were thematically analyzed, resulting in four themes: (1) necessity; (2) impact of employer size; (3) motivators for implementation, and (4) use as an educational tool. Although initially in its early stages, the Standard now provides a key tool to improve accommodations for carer-workers. • Caregiving is highly gendered in nature. • Programs and policies specific to carer-workers should be implemented in light of the rapidly aging and ailing Canadian population. • Staff considered the Carer-Inclusive and Accommodating Organizations Standard (the Standard) is a useful and timely tool for organizations to better support their carer-workers. • The Standard helps foster a culture of care and inclusivity. • The size of an organization affects how the Standard is received and implemented. • To better disseminate the Standard to employers, the business case should be emphasized.
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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 | 0.158 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".