Propagating change: Weaving indigenous knowledge in community and school development
Bibliographic record
Abstract
As long-time cultural workers in working-class BIPOC communities, we have experienced the power of intergenerational, intersectional, panracial solidarity movements. It is through this framework we cultivated and nurtured an indigenous knowledge-centered community of partners from environmental, land back, culture and arts-based, and holistic healing organizations together to build relationships and strategize with educators and other school personnel. We intentionally centered our work in a public high school which has long been written off as underperforming, according to traditional educational metrics. Instead, we collaborated with multi-sector partners and created a hub for culturally-, linguistically-, ecologically-, artistically-, technologically-, and intellectually-thriving opportunities and propagation. We outline the tenets and themes of this project with vignettes to highlight the importance of centering: relationality to the land and the people; culture shifting and realignment; experimentation and openness; interdisciplinary and intergenerational collaboration. The strategies we have undertaken fortify the foundations to bridge solidarities across Indigenous, Black, Pacific Islander, Middle-Eastern, Latinae, and Asian communities that lead to transformative change in teaching and learning, community actualization, and cultural perpetuity.
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.
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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.066 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".