Cross-national work–life research: common misconceptions and pervasive challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While cross-national work-life research is a flourishing field of research, but a recent one, it is relatively recent as national context had been the missing ‘elephant in the room’ of work–life research for decades. Based on the keynote talk I gave at the 2015 Community, Work and Family conference in Malmö, Sweden, this research note highlights three pervasive challenges which I believe need to be discussed in our community of scholars, practitioners and policy-makers so that our research makes the strongest possible impact for individuals and organisations: (1) educating practitioners and policy-makers on the structuring impact that public and employer policies have on individual so-called private work–life decisions; (2) analyzing the inequalities of access to these policies within each country, which are often masked by simplified country-level comparisons and (3) finding innovative ways to combine ambitious etic research designs with in-depth emic understanding of local cultures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it