Forecasting human capital of EU member countries accounting for sociocultural determinants
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
Abstract Inclusion of additional dimensions to population projections can lead to an improvement in the overall quality of the projections and to an enhanced analytical potential of derived projections such as literacy skills and labor force participation. This paper describes the modeling of educational attainment of a microsimulation projection model of the European Union countries. Using ordered logistic regressions on five waves of the European Social Survey, we estimate the impact of mother's education and other sociocultural characteristics on educational attainment and implement them into the microsimulation model. Results of the different projection scenarios are contrasted to understand how the education of the mother and sociocultural variables may affect projection outcomes. We show that a change in the impact of mother's education on children's educational attainment may have a big effect on future trends. Moreover, the proposed approach yields more consistent population projection outputs for specific subpopulations.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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