Bibliographic record
Abstract
This article is presented in two parts. Part I is an overview of the sea change in craft studies among scholars, curators, and artists. It also documents the shift of craft history studies into an emerging post-disciplinary field, still at home academically in art schools and university art history departments, but now greatly influenced by anthropology, ethnography, sociology, material culture, critical theory, women’s studies, and other disciplines. In illustrating this shift, the author compares her experience when employed (1976–1997) as museum librarian at the former Craft and Folk Art Museum in Los Angeles with the current program of the renamed (Craft Contemporary) museum. She also compares three craft history textbooks. Part II describes the author’s search for teachers of craft history and records the results of a survey conducted in May 2021 of twenty-eight craft history teachers in US and Canadian colleges. The comments are so diverse the author could not summarize them, and she includes excerpts from all who answered the narrative questions. Though gender and race bias in craft studies must still be confronted, as in art history studies as a whole, the teaching of craft history is moving toward a global perspective. However, the practical need to break down the global into more manageable parts is a pedagogical and bibliographic challenge.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.010 | 0.043 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".