La elección de asignaturas de ciencias: análisis de los factores determinantes
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
Este artículo presenta unanálisis de la literaturasobre las elecciones de una asignatura científicaen la escuelay los factores influyentes,por la importancia que tienen las elecciones sobre la actual crisis de vocaciones científicas. Los factores que determinan las elecciones son personales, escolares y extraescolares. Entre los primeros, destacan el sexo y las actitudes hacia la ciencia y las materias escolares; ambos aspectos se discuten especialmente. Entrelos segundos, la calidad de la educación científica a través de los currículos, los profesores y la equidad. Losfactores extraescolares son más diversos y numerosos. Finalmente, se sugieren algunas propuestas para mejorar las elecciones de la ciencia,reforzando las intervenciones de orientación académica e innovando la educación científica con una orientación humanística.Descriptores: diferencias de género
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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