Do Fields of Study Matter for Over-education?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Resorting to European Labor Force Survey 2003—2005 data and controlling for factors traditionally accounting for over-education, we demonstrate here that fields of study influence the odds of being overeducated in Spain and in Germany. Being more stratified than the Spanish system of education, the German one uses fields of study as a signaling device for the labor market to a lesser extent than Spanish one. Cross-country similarities in terms of the relative position of fields of study within the country are discussed. Two samples have been researched: a general sample with information about individuals' fields of study as well as a restricted sample with additional information individuals' parental ISEI score, when such information was available. Heckman selection modeling has been applied to the latter (restricted) sample. A new technique has been devised to measure over-education, relying on ISCED categories instead of years of education.
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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 | 0.000 | 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