El desempleo juvenil en España y Castilla y León
Bibliographic record
Abstract
El objetivo del trabajo es analizar el desempleo juvenil en España y Castilla y León, poniendo en contexto todos los rasgos característicos que puedan afectar directa o indirectamente sobre el objeto de estudio. Para ello, se realiza un análisis descriptivo y explicativo tomando como referencia el periodo comprendido entre 2005 y el primer trimestre de 2018. \nCastilla y León en comparación con España, se encuentra en una posición notablemente favorable en lo que a paro se refiere. La tendencia en los últimos años demuestra que el desempleo, tanto en España como en CyL, está registrando un comportamiento positivo, a lo que hay que añadir que en Castilla y León el paro desciende a un ritmo mayor que en España. \nFactores como las deficiencias del sistema educativo y del mercado de trabajo, explican la relevancia del desempleo juvenil en España. Otros factores con menor relevancia que los mencionados anteriormente, son el abandono escolar y la escasa efectividad de las políticas activas de empleo utilizadas para mejorar la situación.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".