Reclaiming Relationality through the Logic of the Gift and Vulnerability
Bibliographic record
Abstract
Abstract This article addresses the conditions that are necessary for non-Indigenous people to learn from Indigenous people, more specifically from women and feminists. As non-Indigenous scholars, we first explore the challenges of epistemic dialogue through the example of Traditional Ecological Knowledge (TEK). From there, through the concept of mastery, we examine the social and ontological conditions under which settler subjectivities develop. As demonstrated by Julietta Singh and Val Plumwood, the logic of mastery—which has legitimated the oppression and exploitation of Indigenous peoples—has been reproduced in academia, leaving almost no room for Indigenous knowledge and epistemes. In the same vein, Sámi scholar Rauna Kuokkanen reclaims and suggests the logic of the gift as a means to render academia more hospitable to Indigenous peoples and epistemes. In our view, reclaim(ing) as a concept-practice is a promising way to disrupt colonial, racist, and sexist power relations. Thus, we in turn propose to reclaim vulnerability as defined by Judith Butler in order to deconstruct masterful settler subjectivities and reconstruct relational ones instead. As theorized by Erinn Gilson, we propose epistemic vulnerability to imagine the conditions of our learning from Indigenous peoples and philosophies.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.099 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".