Culturally and Ecologically Sustaining Pedagogies: Cultivating Glocally Generous Classrooms and Societies
Bibliographic record
Abstract
Generosity is a shared virtue with distinct expressions across cultures and regions. This article engages 26 teacher education students in a/r/tographic exploration of local cultures and ecologies during a 1-week global teacher education program at a large, urban university in China. Participants across eight Chinese provinces/municipalities, and the nations of Brazil, Canada, South Africa, South Korea, and the United States reflected on and shared local cultures and ecologies via photo collage, autobiographical reflection, children’s book creation, and lesson plan creation. This article presents a generosity-inspired theory for culturally and ecologically sustaining pedagogies to demonstrate how local cultures and ecologies shape global norms and understandings and make a case for why such local generosity must be sustained. A/r/tography emerged in this article as a meaningful pedagogical practice for examining, sharing, and appreciating local cultural and ecological generosity across global contexts.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| 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".