Bibliographic record
Abstract
Chapter 3 illustrated the slow pace of change in gender representation in construction and transport in comparison to other sectors. Chapters 4 , 5 , 6 and 7 detailed the difficulties still facing women in entering and remaining in male-dominated occupations, while highlighting some progress made and some of the benefits women felt from working in male-dominated jobs. Where changes in the gender balance and gendered culture of workplaces have occurred, this has often been as a result of proactive strategies and measures intended to overcome occupational gender segregation. This chapter examines a variety of initiatives to encourage women to enter male-dominated occupations and to support their retention, drawing on examples from Canada, the USA, South Africa, the UK and other EU countries. It seeks to identify some of the factors that contribute to increasing women’s participation in male-dominated sectors, highlighting the importance of the legal framework underpinning intervention, as well as enforcement of the law, and the political will to implement change at all levels. The chapter discusses published research from interventions in several national contexts, as well as my own empirical research findings from the UK.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".