PLANTING SEEDS OF HOPE - TRINITIES, ASYMMETRIES, KINSHIP AND SWEETGRASS BRAIDING: Anishinaabe, Lunaapeew and Hebrew Revitalization
Bibliographic record
Abstract
As Canadian settler society grapples with its human rights violations against Indigenous peoples, what might striving to be an ally, to be in good relations look like? In this arts-based auto-ethnographic dissertation, I provide an example of allyship by reflecting on the implications of Old Midewiwin teachings of sweetgrass braiding for (1) revitalization and reclamation of language and culture in Israeli, Anishinaabe and Lunaapeew cultural contexts and (2) allyship with Indigenous revitalization. The centrality of the arts and storytelling are integral to the Sweetgrass Braiding Teachings referenced in this dissertation, and to Indigenous research, knowledge sharing, and language. Following Anishinaabe Old Midewiwin Sweetgrass Braiding Teachings centred on spirit, body, mind, arts, language, mathematics and the Anishinaabe clan morals from Elder and Knowledge Keeper Wendy Phillips, I proceed from the understanding that language revitalization is inextricably linked with the revitalization of culture, with Anishinaabe and Lunaapeew philosophy, worldview, and ways of living. Identifying the interconnectedness of these elements led to my choice of using weaving as the central metaphor that guides my dissertation.Through interviews and dialogues with Israeli artists, interviews and dialogues with Anishinaabe and Lunaapeew Knowledge Keepers and community members, keeping research journals and making field notes, and creating numerous artworks, I explored the revitalization of First Nations language and culture today on Turtle Island, in comparison to the Hebrew revitalization efforts my Jewish ancestors were involved in Palestine of the late 19thC and early 20thC. Intercultural conversations I have had with Knowledge Keepers have yielded reciprocal lessons learned from Hebrew revitalization on the one hand and the revitalization of Anishinaabe and Lunaapew on the other. While the task of raising a new generation of first language speakers is a desirable outcome of revitalization, questioning identity, notions of belonging, as well as the place of spirit, morality, mortality, grief, healing, and environmental sustainability are inseparable facets of this process. Keywords: language revitalization, culture revitalization, Anishinaabemowin, Lunaapeew, Hebrew, arts-based research, Indigenous research methodology, allyship.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".