Work–Life Balance as a Household Negotiation: A New Perspective from Rural India
Bibliographic record
Abstract
Bringing more women into the formal workforce is an important component of corporate strategies, development efforts, and the United Nation’s Sustainable Development Goals. Yet, these policies often do not consider the household work that women already do to support the survival of their families, making work-for-wages impossible or creating time famines for women who attempt to do both. Thus, for women to engage in work-for-wages, they must find a way to alleviate their work-for-households. Using the analytical lens of household decision-making from anthropology, our analysis of working women in rural India shows that, far from being an individual decision about time allocation, women’s ability to work formal jobs was a family project to reallocate labor. These insights suggest that the focus on the individual in work–life balance literature and policy-making inadequately represents a phenomenon that involves other household members, implicitly or explicitly. It also highlights the need to broaden our definition of “work” to include both the paid and unpaid labor that is vital to people’s survival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".