Work, Care and Policy: Evaluating Carer-Inclusive Workplace Tools to Support Canada's Care Economy
Bibliographic record
Abstract
Carer-employees (CEs)—individuals who balance paid employment with unpaid caregiving responsibilities—represent a growing portion of Canada’s workforce, with over 5.2 million individuals navigating this dual role. This population faces considerable challenges to their mental, physical, and economic well-being. In response, a number of tools and standards have been developed to promote carer-inclusive and accommodating workplace practices. This mixed-methods thesis evaluates the uptake and effectiveness of two such initiatives across Canadian workplaces. Study 1 investigates the adoption of the CSA B701:17 (R2021) Carer-Inclusive and Accommodating Organizations Standard and its accompanying handbook. Despite the standard’s potential to guide employers in supporting CEs, uptake has been minimal since its 2017 release. Using a purposive sampling approach, the study collected survey data (n = 71) and conducted semi-structured interviews (n = 11) with Canadian employers. Descriptive statistics and logistic regression analysis were used to assess predictors of formal uptake, while qualitative thematic analysis identified common workplace policies and barriers. Findings reveal that only 24% of respondents had implemented the Standard, with existing support structures and full implementation status being strong predictors of uptake. Thematic results highlighted the crucial role of workplace culture in supporting or hindering caregiver-friendly practices. Study 2 evaluates a national knowledge mobilization (KMb) campaign aimed at increasing awareness and uptake of caregiver-friendly workplace practices (CFWPs). Phase I of the campaign involved the publication of four articles in leading national industry magazines targeting human resources professionals, occupational health and safety professionals, and small-to-medium-sized business employers. Phase II featured a three-part webinar series designed to complement the articles. Engagement metrics—collected via social media analytics, website data, and registration systems—were analyzed to assess campaign reach and effectiveness. In total, the campaign garnered over 36,000 views, 2,469 unique views, 55,445 social media impressions, and 432 social media clicks. Article 3, tailored to small and medium-sized businesses, demonstrated the highest level of engagement. Results show that targeted, paid publication efforts had the greatest impact on knowledge dissemination and tool uptake. Taken together, these studies highlight the importance of tailoring tools and dissemination strategies to specific workplace contexts. Future work should prioritize employer engagement and explore mechanisms for embedding caregiver support into organizational culture and policy.
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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 | 0.039 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".