Bibliographic record
Abstract
Exhibition staged as part of the AHRC-funded Exhibiting Fashion research project. \n \nHow are fashion exhibitions conceived, developed, delivered? The Exhibiting Fashion research project has been looking into these questions using live observation and analysis of collaborative practice-based research. \n \nThis exhibition looks at some of the processes and principles that underpin the project. \n \nThe practice-based research centred on production of three fashion exhibitions developed through the collaborative exhibition-making and curatorial practices of the project participants. \n \nUnpicking Couture, Manchester Art Gallery, Manchester, ends 12 January 2025 \nInspired: the art of making historic fashion, Bankfield Museum, Halifax, ends 21 December 2024 \nThe Drag Show, Beecroft Art Gallery, Southend-on-Sea, ends 13 July 2025 \n \nDevelopment of each exhibition was documented live. Analysis of this documentation (along with data gathered through interviews, participants’ journals and sketchbooks, workshops and evaluation) has informed an Exhibiting Fashion Toolkit. \n \nThe toolkit will support non-specialist curators in small and mid-sized museums to create innovative, accessible, resource-efficient fashion displays.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.385 | 0.081 |
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".