The stratification of education systems and social background inequality of educational opportunity
Bibliographic record
Abstract
This article aims to identify the moderating effect of two dimensions of the stratification of education systems (the extent to which the first selection is based on students’ ability and the age of first selection) on social background gradient in educational attainment. Individual-level data of the European Social Survey (round 1 to 9) is complemented with new contextual indicators measuring various education systems’ characteristics. This article’s contribution to the debate is twofold. First, it simultaneously investigates two dimensions of the stratification of education systems that have never been analyzed in cross-country studies investigating long-term educational outcomes. Second, it provides a series of indicators of education systems’ characteristics collected by means of an online expert survey whose validity and reliability is also tested. Findings show that the two dimensions of the stratification of education systems have opposite effects. As the first selection is increasingly based on students’ ability, social background gradient in educational attainment increases. In contrast, postponing the age of first selection decreases social inequality in educational opportunity.
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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 | 0.004 |
| 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 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".