Bibliographic record
Abstract
Abstract Awareness of the influence of culture has permeated work–family research since its inception. In this chapter, we first briefly review the history and evolution of cross-cultural work–family research, followed by a focus on the current state of work–family research in the last decade. Although cross-cultural work–family research has experienced stunning growth over the last three decades, it still tends to be heavily centered on a limited set of constructs (i.e., work–family conflict), use a narrow range of methods (i.e., quantitative cross-sectional survey research), concentrate on certain world regions (i.e., Anglo-Asian comparisons), and predictions are based predominantly on specific cultural values (i.e., individualism–collectivism). We identify key controversies in the literature and set an agenda for future research that expands our understanding of cross-cultural work–family concerns in multiple ways, including a call for a focus on process to refine theory-building and theory-testing and diversification of research designs and methods (e.g., experiments). Implications for theory and practice are also discussed.
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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 | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".