Matrilineal inheritances through Modernism, Feminism & the Arts, from the Pageants of Noble Women and Famous Women dinner service to the present
Bibliographic record
Abstract
Our collaboration came about thanks to a Canadian colleague, Professor Maria DiCenzo, whose current work focuses on interwar feminist media. Professor DiCenzo became aware of Hana Leaper’s research into the kinds of historical precedents that had inspired and informed the portraits of 48 historical women featured on Vanessa Bell and Duncan Grant’s Famous Women plates and connected her with another British scholar working at a nearby UK university. Dr Amy Binns is a senior lecturer in the School of Journalism, Media and Performance at the University of Central Lancaster, who as well as researching practical solutions for difficult online behaviour, has begun to publish on the role of interwar pageants of noble women in recording and celebrating women’s histories. \n \nThe two projects have a number of key similarities – and even more intriguingly, a number of thought-provoking differences. Whilst the Famous Women plates were created by two canonical artists as a commission for a powerful and influential collector, the pageants of noble women were produced by women’s community groups for very localised audiences. This paper will explore not only the conditions and effects of these projects, but questions about how we select and celebrate our idols, and the lasting of this lineage of Modernism, Feminism and the Arts in transcribing overlooked histories. \n \nWe will proceed to describe and analyse the participatory public art programme, the ‘Famous Women Project’ that we co-curated and stage at Tate Liverpool in April 2019. The aims of the project were to commemorate and promote the dissident histories uncovered in the Pageants of Noble Women and the Famous Women dinner service in the context of an art gallery, and also to provide both historical and contemporary counterpoints to some of the ways the media chooses which figures are worthy of celebration.
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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 | 0.015 | 0.034 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".