Equity in the workplace: gendering workplace policy analysis
Bibliographic record
Abstract
Chapter 1 Preface Chapter 2 Introduction Part 3 Theoretical Perspectives on Gender and Workplace Policy Chapter 4 Globalization, Gender and Work: Perspectives on Global Regulation Chapter 5 Policy Strategies in a Global Era for Gendered Workplace Equity Chapter 6 Institutionally Embedded Gender Models: Re-regulating and Breadwinner Models in Germany and Japan Chapter 6 European Gender Mainstreaming: Promises and Pitfalls of Transformative Policy Part 7 Implications of Gender in the Workplace Chapter 9 Parental Leave and Gender Equality: What Can the U.S. Learn from the European Union? Chapter 9 Career Advancement Choices of Female Managers in U.S. Local Government Chapter 10 An Assessment of Women's Acceptance as Breadwinners Chapter 11 The Employment Insurance Model: Maternity, Paternal, and Sickness Benefits in Canada Part 11 Reconciliation of Work and Family Life: Maternity, Parental, and Family Leave Chapter 12 Erosion of the Male-Breadwinner Model? Female Labor-Market Participation and Family-Leave Policies in Germany Chapter 13 Solving a Problem or Tinkering at the Margins? Work, Family and Caregiving Chapter 13 Globalization and Work/Life Balance: Gendered Implications of New Initiatives at a U.S. Multinational in Japan Chapter 14 Europeanizing the Military: The ECJ as a Catalyst in the Transformation of the Bundeswehr Part 17 Specific Applications of Workplace Policies: Gender in Equity in the Workplace Chapter 19 Implementing Sexual Harassment Law in the United States and Germany Chapter 20 Sexual Harassment Policies and Employee Preferences in Local U.S. Government
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".