Bibliographic record
Abstract
In 1988 the authors published a paper in an edited volume on women and paid work that brought together analyses of the statistical resources available to researchers at that time, including the recently-completed Women and Employment Survey, in which they assessed the impending prospects for greater gender equality in employment1. In this paper, they reassess this historical evaluation of prospects for gender equality in employment. Drawing on recent work, they investigate the impact of increased access to higher education on gender divisions of labour throughout the last 25 years. In the context of economic restructuring and the ICT revolution, `they examine trends in participation in higher education and explore occupational change. From national survey data sources, including their own longitudinal surveys and interviews with graduates who entered the UK labour market in the latter half of the 1990s, they examine the relationship between higher education, employment, career development, partnership and family-formation. How far has increasingly equal access to educational opportunities resulted in equal employment outcomes a quarter
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.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".