Fashioning DIY digital archives: Unsettling academic research to centre garment workers’ voices
Bibliographic record
Abstract
Recent calls for decentring Eurocentric frameworks across fashion studies, alongside growing commitments to worker rights, calls for a circular economy, waste reduction and more sustainable materials draw attention to the complex and intractable social, environmental and political challenges facing the global sector. Here we point out how academic research is also implicated in reproducing inequalities, through practices of data collection, analysis and knowledge dissemination. Specifically, in the case of fashion, how worker representation, and indeed worker control over representations of their lived experiences, including labour activism, is lacking in academic research. In this article, we argue that DIY Academic Archiving can be utilized by academics, including fashion scholars, as a powerful tool for remaking fashion research. We propose unsettling usual practices around data management, as well as redirecting current moves for open research data. Turning instead to inspiration from radical archival theory and practice, we explore the potential for co-creating open-access digital archives of research data – here workers’ own stories – to open up possibilities for workers to be more involved in the creation of public narratives about fashion. While not a panacea for resolving all the ills of the fashion industry, we see research processes where workers have more control over their own stories, and how they are used, as a critical step in reimagining fashion scholarship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".