Knowledge versus Education in the Margins: An Indigenous and Feminist Critique of Education
Bibliographic record
Abstract
This article highlights the perceptions and expectations of knowledge that many people, including educators and policy makers, take for granted. Our focus of understanding is Indigenous studies and gender studies. Our aim is to show how modern education undermines these fields of studies. We use an autoethnographic method, reflecting more than 75 years as pupils/students and more than 90 years as educators. We have carefully chosen narratives of exposure to knowledge outside the educational system, as well as narratives of limitations posed upon us by the educational system. This narrative approach makes it possible for us to investigate and discuss our grief about areas of knowledge that society cries for, but the educational system continuously finds ways to resist. Our conclusion is that crucial knowledge is located outside the educational system, where individuals, groups, and communities cherish, protect, and guard knowledge that the educational system marginalises or excludes. As this knowledge is fundamental for life, our message is that the educational system needs to re-evaluate its strategies to stay relevant.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.118 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| 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".