Mend + Transform + Renew: Reactivating and (re)imagining pre and post consumer textile waste
Bibliographic record
Abstract
The intention of this paper is to identify mending as an artistic practice able to\nfunction as a tool for creation, transformation and (re)imagination. The discussion\nwill contextualize my practice as an artist and designer working with pre and\npost consumer textile waste in relation to mending as an artistic practice. From\nthe tools I utilize to the artisanal applications I explore, Vancouver has influenced\nmy use of mending as tool for investigating, creating and (re)imagining discarded\nclothing and textile industry waste.\nMy research uncovers how mending contributes to the construction of identity\nthrough a non-consumption based practice where I focus upon reactivating and\ntransforming the discarded, devalued and obsolete. I position my thesis in\nalignment with Otto Von Busch’s theory on Fashion Hactivism alongside artists\nsuch as Michael Swaine, Liz Collins, Eleanor Ray, Jonnet Middleton and\nTomofHolland. As part of the growing discourse surrounding mending,\ntransformation and reactivation, my role as a mending practitioner draws upon\nthe ability to tune in, observe and reverse engineer from a set of limited\nresources and circumstances where I can (re)imagine and allow the invisible to\nbecome visible.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".