From “nobody's clapping for us” to “bad moms”: COVID‐19 and the circle of childcare in Canada
Bibliographic record
Abstract
The COVID-19 pandemic has highlighted the importance of childcare to national economies in general and women's economic participation in particular, spurring renewed interest in childcare policy in many countries that have implemented lockdowns. This paper adopts a circle of care framework to analyzes how COVID-19 has affected paid childcare, unpaid childcare and other paid work, and the relationship between these sectors. Analysis is grounded in the lived experiences of parents and childcare educators, documented through 16 semi-structured interviews during the initial lockdown (March-June 2020) in British Columbia, Canada. Experiences from educators suggest their safety was not prioritized, and that their contributions were undervalued and went unrecognized. Mothers, who provided the majority of unpaid care, not only lost income due to care demands, but struggled to access necessities, with some reporting increased personal insecurity. Those attempting to work from home also experienced feelings of guilt and distress as they tried to manage the triple burden. Similarities of experiences across the circle of care suggest the COVID-19 childcare policy response in BC Canada downloaded care responsibilities on to women without corresponding recognition or support, causing women to absorb the costs of care work, with potential long-term negative effects on women's careers and well-being, as well as on the resilience of the circle of care. Pandemic recovery and preparedness policies that aim to promote gender equality must consider all sectors of the circle of care and the relationships between them.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.049 | 0.014 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".