The Needed Messy Practice Ground for Curricular Un/Decolonizing and Indigenizing
Bibliographic record
Abstract
In this five-year co-curricular-making project, participants individually and collectively engage in the messiness of ongoing meaning-making. Such curricular terrain acknowledges the particulars of individuals and place to provide the needed context as 100+ practicing and 140+ prospective educators seek un/decolonized and Indigenized co-curricular pathways. The documentation of educators’ increasing cognizance of the relational interdependency of seeing with acting in classrooms reorients and furthers learners and learning. Modes of being with associated habits and practices emerge, revealing potential within the capacity of reciprocity for education’s reparation and renewal, forming the necessary messy practice ground for long-term investment in curricular un/decolonization and Indigenization.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".