The Intersection of Work and Care: Exploring the Facilitators and Barriers of Maternal Employment in Canada
Bibliographic record
Abstract
Since the 1970s, many OECD countries have seen a significant increase in maternal employment rates. In cross-national comparison, Canada has high maternal employment rates, but lags behind some Nordic and East European countries. Within this context, this study explores how larger social, cultural and policy environments shape mothers' employment experiences, challenging the notion that women prefer to opt out of the labour force when they have children To conduct this analysis, I drew on focus groups (n=19) and individual interviews (n=39) with 58 mothers in Canada with preschool children in the province of Alberta. The key finding from this study was that the majority of mothers, despite wanting to continue their careers alongside parenthood, experienced challenges integrating unpaid and paid work. To navigate these challenges, mothers employed various strategies, including seeking flexibility at work, reducing work hours, or opting out of employment. Yet, many remained ambivalent regarding their employment arrangements. I detail the ways in which paid parental leave and childcare policies acted as facilitators or barriers to mothers’ labour force participation. Overall, the findings indicate that current policies are not sufficient to support mothers in the labour force. This study adds to a body of Canadian literature that examines how barriers such as pervasive gender norms in the workplace and households, and workplace inflexibility, create barriers to mothers’ labour force participation and impact mothers’ experiences in the labour market.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.023 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".