Bibliographic record
Abstract
In this essay, I examine how research methodologies can draw from Indigenous peoples’ care work and mobilities to contribute towards Indigenous futurities. I draw on stories of my own research trajectory, that has been shaped by the support of Mushkegowuk women, and bring them into dialogue with Indigenous feminist theorizations of futurities, relationalities, care ethics and movement. I examine how methodologies of care can act as extensions of relations of care, and in the process, activate the complexities and expansiveness of Indigenous community, or what I call Indigenous relational geographies, through movement across lands and waters. I reflect on how Indigenous movement is learned and embodied through relations with the non-human world by grounding my discussion in the significance of water relations in the muskegs in so-called northern Ontario Canada and how they have helped me understand Mushkegowuk kinship relations as rippling out in and beyond that region. Overall, I am interested in how mobile relations of care evoke full and fluid conceptions of Indigenous kinship that exceed colonial spatialities, and end by considering how these relationships are crucial in shaping the visions and material relations of Indigenous and anti-colonial futurities moving forward.
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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 | 0.023 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.071 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".