Struggle and the Politics of Self Care: A Curatorial Perspective
Bibliographic record
Abstract
“Take Care of Your Self” is a research-creation project that explores the potential for transcultural dialogue and engagement through the concept of “Care-full curation.” To explore these ideas through research-creation I organized a week-long exhibition and series of events held during the summer of 2017 in Montreal titled “Take Care of Your Self: A Transcultural Art Event”. The exhibit, in which I was both participating artist and curator, featured work by 27 artists of colour, or “othered” artists from diverse communities. The exhibit sought to explore how notions of self-care, self-determination and healing have conceptually informed artists from a wide range of cultural orientations who are dealing with complex issues of personal, social and political struggle. \n \nThrough care-full curation, my intention was to foster counter-narratives to the existing structures perpetrated by mainstream media that keep our diverse struggles separated, and to create a safe space illustrated by artworks and conversations on the subject of self-care and struggle. In this paper, I draw on the concept of self-care as it is articulated and practiced in Black feminist thought and contemporary social movements. I explore how empowerment can be integrated into an approach of critical curation and intersectionality. I also locate the exhibit and series of events in the larger framework of self-care and art as a method of transformative transcultural convening. I position my own practice as an artist-curator through both theory and method by highlighting the process, goals and outcomes of the exhibition “Take Care of Your Self”. \n \n \nKeywords: trauma / healing / empowerment / counter-narrative / social justice / transcultural / convening / intersectionality / safe space / ruptures / marginality
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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 | 0.031 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.050 | 0.192 |
| Scholarly communication | 0.038 | 0.023 |
| Open science | 0.005 | 0.028 |
| Research integrity | 0.012 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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".