Undoing human supremacy and white supremacy to transform relationships: An interview with Megan Bang and Ananda Marin
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
Megan Bang (Ojibwe and Italian descent) is a Professor of the Learning Sciences and Psychology at Northwestern University and is currently serving as the Senior Vice President at the Spencer Foundation. Dr. Bang’s research focuses on the complexities of navigating multiple meaning systems in creating and implementing more effective and just learning environments in science, technology, engineering, arts, and mathematics education. Ananda Marin (African American, Choctaw [non-enrolled], European American descent) is an Assistant Professor of Social Research Methodology in UCLA’s Department of Education and faculty in American Indian Studies. Her research explores questions about the cultural nature of teaching, learning, and development. This interview with two Indigenous scholars provides educators with a chance to explore the possibilities of Indigenous worldviews on their climate change praxis. The scholars ask educators to consider how white and human supremacy are perpetuated in current educational paradigms. They discuss the necessity of transformations between relationships between humans and the natural world in fighting climate change. Bang and Marin underline the importance of education that immerses children in learning with places, paying attention to embodied, relational, axiological, and world-building dimensions of storying with lands.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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