La pedagogía crítica no es una receta: Estrategias, desafíos y aportes en la enseñanza de los Estudios Sociales. Entrevista con el Dr. E. Wayne Ross
Bibliographic record
Abstract
This article presents the results of an interview with Dr. E. Wayne Ross, who is a professor and researcher at the University of British Columbia in Vancouver, Canada. He has also worked with various institutions such as the State University of New York, the University of Louisville, and Binghamton University. His areas of interest include social studies education, curriculum studies, democratic education, and critical pedagogy. The interview with Dr. Ross is focused on various conceptualizations surrounding critical pedagogy, as well as the contributions, challenges, and obstacles involved in a critical approach to social studies education. Additionally, the interview explored strategies that teachers can implement in their classrooms to break away from the traditional education paradigms.
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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 | 0.088 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.021 | 0.081 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".