LABOR MARKET DISCRIMINATION – ARE WOMEN STILL MORE SECONDARY WORKERS?
Bibliographic record
Abstract
Discrimination based on gender is commonly observed on labor markets, although its scale and symptoms are different with regard to country and are subject to changes over time. Gender-related diverse flows on the labor market constitute one of its symptoms. The paper’s main objective was to answer the question whether women on the labor market were still secondary workers. The analysis was conducted based on general models of flows on the labour market, examining connections between changes in a number of unemployed and changes in a number of employed men and women. There were applied data for eight OECD countries from various regions of the world. The obtained results were highly diversified depending on the analysis period and country. However, they confirmed that in the past women had been more secondary workers despite no differences in the unemployment rate. Gender impact was noticeable especially in the employment decrease periods. For data after the year 1990, gender-related differences disappeared or significantly decreased in four countries (Australia, Denmark, United Kingdom, United States), but in two of them (Canada, South Korea) – differences increased.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".