Waste and Wasted Opportunity: Utilizing Archive Collections at the Victoria and Albert Museum to Inform Contemporary Sustainability
Bibliographic record
Abstract
This paper explores forgotten material histories and how they can be harnessed to inform sustainable textile design and help us to combat our current climate crisis.Two now defunct collections at the Victoria and Albert Museum (V&A)-the Animal Products collection and the Waste Products collection-provide an insight into ideas around waste, resource, and sustainability in Victorian Britain.These archival collections contain resources and technologies designed to tackle problems such as material shortages and wasted by-products that warrant reinvestigation.The research for this paper was developed in three stages: first, the collections were surveyed to quantify and build a complete picture of their contents; second, the background and motivations of the display's curator, Peter Lund Simmonds, were investigated to further understand Victorian ideas around waste and material potential; and third, shoddy was identified as a case study to further understand the contemporaneous significance of the displays.Despite the prevalence of the shoddy industry, few examples survive in museum collections today.However, this research demonstrates that the V&A's collection once held numerous examples of shoddy and examines why these materials were deaccessioned and destroyed.Shoddy manufacturing processes and societal attitudes are explored to further understand these curatorial decisions decipher lessons for contemporary textile recycling from this historical paradigm.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".