Inequality in educational transitions: the case of post-compulsory education in Spain
Bibliographic record
Abstract
This paper seeks to identify mechanisms that may underpin part of the observed association between class of origin and educational attainment in the Spanish case. In line with a well established strategy in the field of social stratification sociology, we analyze educational attainment as the outcome of a sequence of transitions at each of which a student can drop-out or move on to the next educational level. According to this approach, the paper aims at making three contributions to the study of inequality of educational opportunities by means of an analysis of class inequality in the transition to post-compulsory education in Spain. First, it deals with the impact of social class on academic performance in terms of educational failure in compulsory secondary education. Second, it monitors the case of an educational �failure� during compulsory education and assesses social class effect on retaking rates after failing. And, third, the paper analyzes class differences in the choice of the academic track (bachillerato) versus the vocational training track (FP) among students who have completed compulsory education on time. In doing this, it addresses the «diversion thesis» according to which working class students might be diverted from the academic track, with negative consequences for later access to the university, because vocational training offers an attractive short-term option for them. The empirical analysis is based on data collected from the first quarter of Spanish Labour Force Surveys for the years 2005, 2006, 2007 and 2008. Our results find some support in the Spanish case for the three hypotheses put forward in the paper: not only significant class differences can be found among students of different social origins in the probability of completing compulsory secondary education on time, but clear class effects can also be seen in retaking rates after failure and in opting for vocational training track after completing secondary compulsory education.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".