Inclusion and exclusion factors in adult education of youth with a low educational level in Spain
Bibliographic record
Abstract
In this paper we analyse, from a biographical perspective, youth participation in education and training, aged between 26 and 28 years, who have no qualifications or at most have a qualification corresponding to the Lower Secondary Education Certificate (LSEC) (ISCED 0-2), during the 10 years elapsed between the end of compulsory education (2000) and the time of the interview (2010). As regards their personal life stories, we cover a broad period which includes different stages in the transition into adulthood, stages which take place in a historical context in which we have moved from a time characterised by ease of access to employment among youth with a low educational level to another time in which youth unemployment levels affects over half of the workforce aged 16 to 24 and in which public policies supporting training and social and professional insertion of young people with a low educational level have been reduced.
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How this classification was reachedexpand
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".