The Vertical Dimension of Occupational Segregation
Why this work is in the frame
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Bibliographic record
Abstract
This article presents a new approach to measuring the most important dimension of gender segregation - the vertical dimension-in quantitative survey data. This, in turn, allows for a reassessment of the view that high levels of gender segregation are synonymous with high levels of social inequality. In order to do this, the article also draws upon significant conceptual developments. `Segregation' as it is commonly understood is named as `overall' segregation, and is the resultant of two components, `horizontal' and `vertical' segregation, representing difference and inequality separately. This provides a clear approach to measurement. The argument is developed with a case study of the British labour force. The pattern of segregation, in terms of its overall level and its components, varies considerably across sections of the labour force. In terms of inequality, the vertical components measured indicate that British women working full-time are more advantaged than we would expect, and that women working in part-time manual occupations, though facing the greatest relative disadvantage in terms of pay, are actually slightly advantaged over men working in manual occupations in terms of social stratification. Although overall segregation has remained relatively unchanged over the five year period from 1991 to 1996, there have been some significant changes to its components within the various sections of the employed British labour force in that time. By looking at the various sections of the labour force, relative to the labour force as a whole, we can achieve a better understanding of how segregation operates with respect to gender inequalities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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