Bibliographic record
Abstract
Citation (2015), "List of Contributors", Gender Segregation in Vocational Education (Comparative Social Research, Vol. 31), Emerald Group Publishing Limited, Bingley, pp. ix-x. https://doi.org/10.1108/S0195-631020150000031014 Publisher: Emerald Group Publishing Limited Copyright © 2015 Emerald Group Publishing Limited Lesley Andres Department of Educational Studies, University of British Columbia, Vancouver, British Columbia, Canada Hans-Peter Blossfeld European University Institute, Florence, Italy Pepka Boyadjieva Institute for the Study of Societies and Knowledge, Bulgarian Academy of Sciences, Sofia, Bulgaria Sandra Buchholz Department of Sociology, University of Bamberg, Bamberg, Germany Pierre Doray Département de sociologie, Université du Québec à Montréal, Montréal, Canada Verena Eberhard Federal Institute for Vocational Education and Training, Bonn, Germany Katarzyna Haverkamp Institute for Small Business Economics, University of Göttingen, Göttingen, Germany Kristinn Hegna Department of Education, University of Oslo, Oslo, Norway Steffen Hillmert Department of Sociology, University of Tübingen, Tübingen, Germany Petya Ilieva-Trichkova Institute for the Study of Societies and Knowledge, Bulgarian Academy of Sciences, Sofia, Bulgaria Christian Imdorf Institute of Sociology, University of Bern, Bern, Switzerland Yuliya Kosyakova European University Institute, Florence, Italy Stephanie Matthes Federal Institute for Vocational Education and Training, Bonn, Germany Ashley Pullman Department of Educational Studies, University of British Columbia, Vancouver, British Columbia, Canada Liza Reisel Institute for Social Research, Oslo, Norway Petrik Runst Institute for Small Business Economics, University of Göttingen, Göttingen, Germany Joanna Sikora School of Sociology, Australian National University, Canberra, Australia Jan Skopek European University Institute, Florence, Italy Emer Smyth Economic and Social Research Institute, Dublin, Ireland Stephanie Steinmetz Department of Sociology, University of Amsterdam, Amsterdam, Netherlands Rumiana Stoilova Institute for the Study of Societies and Knowledge, Bulgarian Academy of Sciences, Sofia, Bulgaria Moris Triventi European University Institute, Florence, Italy Joachim Gerd Ulrich Federal Institute for Vocational Education and Training, Bonn, Germany Book Chapters Gender Segregation in Vocational Education Comparative Social Research Gender Segregation in Vocational Education Copyright Page List of Contributors List of reviewers Editorial Board Preface Gender Segregation in Vocational Education: Introduction Part I: International Comparisons Gender Inequalities at Labour Market Entry: A Comparative View from the eduLIFE Project Vocational Training and Gender Segregation Across Europe Educational Systems and Gender Segregation in Education: A Three-Country Comparison of Germany, Norway and Canada Gender Segregation in Occupational Expectations and in the Labour Market: International Variation and the Role of Education and Training Systems Part II: Intra-National Comparisons Regional Gender Differences in Vocational Education in Bulgaria Explaining the Dynamics of Occupational Segregation by Gender: A Longitudinal Study of the German Vocational Training System of Skilled Crafts Part III: Educational Choices and The Life Course The Need for Social Approval and the Choice of Gender-Typed Occupations Two Sides of the Same Coin? Applied and General Higher Education Gender Stratification in Canada Gender Segregation in Australian Science Education: Contrasting Post-Secondary VET with University About the Authors
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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.744 | 0.751 |
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".