Social Justice in the Domestic Realm: Time Poverty and Wellbeing during the COVID-19 Pandemic
Bibliographic record
Abstract
The concept of time poverty is useful for investigating the widely reported exacerbation of gender inequality in families during COVID-19 pandemic lockdowns. I explore the nature and frequency of this situation in Ontario, Canada to assess domestic inequality, free time, and gendered wellbeing as issues of social justice. Between January and June, 2021, I administered online time use surveys to 100 self-identified women and 100 self-identified men who were living with a spouse and had at least one child learning remotely. The combined responsibilities for the household, childcare, and children’s online learning were overwhelming for the vast majority of women. Consequently, their general experience in the context of the pandemic was one of intensified “time poverty,” a condition I conceptualize as incorporating paid work, the “patriarchal dividend” in domestic task allocation, the endless nature of feminized care-related responsibilities, and women’s consequent lack of recuperative leisure. I assess the nature of leisure, its importance to wellbeing, and the impact of its shortage on women’s lives. Finally, I consider theories of social justice that can illuminate and rectify the imbalances entrenched in gendered divisions of labour within families. The study contributes to pandemic and time poverty literatures, and to the social justice literature by identifying time poverty as an aspect of social injustice in the pandemic context.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".