Negotiating the Cultural Terrain in Transforming Classrooms—The LEAP MODEL
Bibliographic record
Abstract
This study recentres the sociocultural in culturally transforming pedagogic settings whilst foregrounding culturally responsive teaching (CRT). Through a protracted anthropological excavation, teachers’ experiences in a culturally diverse integrated high school were explored and interpreted vis-à-vis tenets and precepts of CRT. Findings from observation and interviews indicate that the pedagogic settings as structured by the teachers were not attendant to the aspirations of CRT and teacher practices were not reflective of dispositions of CRT. Teachers professed negative experiences of the pedagogic setting, demonstrated and professed limited knowledge of the cultural being of their learners. The findings highlighted the need for micro-context cultural excavations to remedy socioculturally detached teaching. Cognisant of the emergent need for a learning tool, the LEAP model is proposed premised on centering the humanistic world of the learners and the inherent currency in their culture for progressive teaching and learning engagements.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.046 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".