Bibliographic record
Abstract
In this transdisciplinary study, the author explores mother-centered cultures and how they are represented in curricula. Matricultures are egalitarian cultures founded on the maternal value of caring relationality. Matricultures embed the maternal in their cultural cosmologies and respect mothering as a condition for cultural continuity. This is the first Canadian curricular study related to matricultures. Answering George Sefa Dei’s call to transgressive educators, this chapter exposes and deconstructs Modernity/coloniality’s systems of domination that subjugate knowledges of ancient and extant matricultures. Re-storying matricultures is transgressive when it exposes the methods by which colonizers imposed European heteropatriarchy on the cultures they colonized. The author’s Listening for Silences methods for researching subjugated knowledges are based on Bacchi’s critical approach to policy analysis, which assumes that the absence of policy discourse around a social problem is an indicator that it has been rendered invisible, has not been problematized, and thus cannot be interrogated. Strategies for re-storying learning about matricultures include (a) interrogating the intersectional impacts of Modernity/coloniality’s systems of domination, (b) problematizing the imposition of Eurocentric heteropatriarchy on Indigenous matricultures in Canada, (c) studying Earth-centered philosophies and non-Abrahamic religions for evidence of the maternal in cosmology, and (d) exploring the diversity of Indigenous matricultures in Canada.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".