Stitching Language: Sounding Voice in the Art Practice of Vanessa Dion Fletcher
Bibliographic record
Abstract
This paper engages with the artistic practice and work of Vanessa Dion Fletcher (Potawatomi and Lenapé) from my perspective as a non-Indigenous academic and curator. Dion Fletcher and I have worked together over the past several years through discussions about her work, studio visits, and various events. In her art practice, Dion Fletcher uses porcupine quills and menstrual blood to inquire into a range of issues and concepts including Indigenous language revitalization, feminist Indigenous corporeality, Land as pedagogy, decolonization, and neurodiversity. In particular her work confronts the ways that Indigeneity, the queer and gendered body, and disability are rendered expendable. In this paper I engage with Dylan Robinson’s “sovereign sense”: a transcorporeal mode of perception that is affective, land-based, and formed through relations between human and non-humans. Dion Fletcher’s work makes palpable this sense of sovereignty through its unruly and mutating feltness. Further, her work makes visible feminist Indigenous artistic acts of resurgence alongside the frictions at the intersections of settler colonialism and disability. Following Karyn Recollet, I contend that Dion Fletcher’s work activates an Indigenous affective experience of futurity and creative intimacy that in turn imagines disability and Indigeneity as sites through which new pedagogical relations can be formed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".