¿Cómo la escuela educa para una ciudadanía activa?: una experiencia de educación cívica ciudadana en Canadá
Bibliographic record
Abstract
Aun cuando educar ciudadanos activos que participan en la vida democratica es un objetivo fundamental de la educacion, en general, y de la Educacion Civica Ciudadana, en particular, hay muy pocas investigaciones empiricas que nos informan como la escuela educa para tal fin. Este estudio, conducido en tres aulas de Educacion Civica en Ontario, Canada, investiga en que medida y como los profesores educan ciudadanos activos, civicamente comprometidos. Haciendo uso de las teorias de la ciudadania activa como marco teorico y metodos etnograficos incluyendo observaciones de clases y entrevistas con profesores y alumnos, los resultados del estudio revelan que las concepciones de quien es un ciudadano activo y los roles que desempena en la vida publica influyen grandemente en como los profesores educan para la ciudadania activa. En la practica, hay tres distintas concepciones de la ciudadania activa que enfatizan (a) el deber civico, (b) hacer una diferencia positiva, y (c) una participacion de orientacion politica. El articulo concluye con una discusion de las implicaciones de los diferentes enfoques para la educacion para la ciudadania democratica.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.043 | 0.011 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".