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
Abstract How people negotiate the work–life interface remains a popular topic for scholars and the public. Work–life research is a large body of interdisciplinary scholarship that considers how people experience, navigate, and negotiate different roles, commitments, and boundaries within and across life domains—often with the goal of improving individual, organizational, and social well-being and success. Spurred by demographic, social, economic, and technological changes, scholars take difference perspectives on overlapping research areas which include work–life balance, work–life conflict, work–family conflict, boundary management, work–life enrichment or facilitation, as well as positive or negative spillover. Key issues addressed include the implications of framing work–life as a dichotomy, drivers of work–life outcomes, how ideals shape work–life negotiations, how individuals negotiate everyday work–life challenges and opportunities, and the influence of evolving information and communication technologies on the work–life interface. Research from multiple disciplines highlights the demographic, economic, moral, cultural, and national factors that affect work–life practices, processes, policies, tactics, and outcomes. This multidisciplinary perspective provides relevant insights for generative research and resilient practice for individuals, groups, organizations, or societies.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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