Colour catch: Aesthetic experiences through West African textiles and nature
Bibliographic record
Abstract
This exhibition is made up of three distinct collections, therefore, it is a collection of collections. The first are Ghanaian textiles collected by Gwenna Moss (1975-77) and Marie Dunn (1971-77) while they were living and working at the Department of Home Science at the University of Ghana during the 1970s. During their stay in Ghana, Gwenna and Marie collected many textiles because of the prestige and symbolic value of textiles in Ghana. For example, on one trip to Nigeria in October 1976 Gwenna acquired the Adire fabrics. Both Gwenna and Marie are professors emeriti. The second are butterfly, moths, beetle and shell specimens collected by Tom Terzin. Tom’s collection includes over 80 drawers of specimens and hundreds of specimens that need to spread. The majority of Tom’s collection was purchased on eBay, where he looked for specimens with aesthetic appeal including colours and morphologies. Tom is currently a professor of Biology at Augustana, University of Alberta. The third collection is artifacts and textiles from the Human Ecology Clothing and Textiles Collection housed in this building at the University of Alberta. The majority of the pieces shown in the exhibition were acquired and collected specifically for the Clothing and Textiles Collection by Mari Bergen. Mari completed her MSc on textiles in Ghana titled ‘Kente cloth weaving among the Asante in Ghana: A West African example of gender and role change resistance’ in 1998. Mari is an avid collector of antique textiles, dolls, maps and other artifacts that provide research opportunities. Hosted by The University of Alberta, Department of Human Ecology, April 8-July 20. 2014, Edmonton, Canada
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".