The effect of different types of education on the likelihood of employment in 29 post-communist countries of Eastern Europe and the former Soviet Union
Why this work is in the frame
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Bibliographic record
Abstract
Purpose The purpose of this paper is to study the effects of a variety of levels of education, namely, high school, vocational and university education, on the probability of being employed in Eastern Europe and the former Soviet Union. Design/methodology/approach The data are from two waves of the Life-in-Transition Survey that covers 29 post-communist transitional countries. The number of binary logistic models is estimated to quantify the effects of different types of education on the likelihood of being employed, while controlling for different sets of covariates. Findings The findings reveal that the effect of employment associated with university education is higher than that of vocational education, which in turn is higher than that of high school education. However, the differences between the effects of the various levels of education are not considerable. Any specific level of education is always associated with a higher effect in Eastern Europe as compared to the former Soviet Union. The effect of education is also found to be higher for females than for males. In the former Soviet Union, the positive effect of university and vocational education on employment is found to go down with age. Originality/value This is the first study which compares effect of different types of education on probability of being employed on a diverse sample of 29 post-communist countries over the period of five years.
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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 | 0.001 | 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