Living to Work (from Home): Overwork, Remote Work, and Gendered Dual Devotion to Work and Family
Bibliographic record
Abstract
Contemporary North American work culture is characterized by experts as one of overwork. Throughout much of the previous century, many parents devoted themselves either to their careers, or to their families. These "competing devotions" served as a cultural model for making sense of the world and alleviated the tension between overwork and family life. Data from interviews with 84 IT workers are used to examine whether devotion to work and family is still experienced as oppositional for working parents. I find that interviewees report feeling devoted both to their families and their careers, which I refer to as dual devotion. Such espousals of dual devotion are facilitated by the use of flexible work policies-remote work and flextime-which enable those with dual devotions to accomplish work-life integration. However, whereas men perceive remote work as allowing them to dedicate more time to childcare, women perceive it as allowing them to dedicate more time to work. These findings advance our understanding of the relationship between gender inequality and the experiential dimensions of work and family time: the practices that enable dual devotions, in particular remote work, help parents maintain an orientation to time that makes overwork more palatable. In either case, workplaces win since women are working long hours and men are not sacrificing paid work hours to take on more childcare or housework.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".