Bibliographic record
Abstract
"As climate change, war, social injustice, gender and racial inequality, unchecked technology and exploitative capitalism remain urgent issues, the worldwide craft community has responded in notable ways. In this follow-up to Craft is Political, D Wood and contributors demonstrate how global circumstances have given rise to additional craft scholarship that further interrogates the political agency of craft. With extensive global focus, this book features twenty-two essays on craft and politics that transcend the familiar Euro-American canon and demonstrate change through craft. Particular attention is brought to the Global South with authors writing about Brazil, Chile, India, Laos, Malaysia, Morocco, Nigeria and Thailand. Chapters look at the erasure of Moroccan women weavers' stories and digital archiving of Black craftspeople in the USA. They explore pottery and eel pots critical to the identity of Virginian Indian tribes, and women's roles in Nigeria as depicted in ceramic art. One author reveals the revival of traditional practices in Laos, and another the increasing recognition of previously-maligned Sami people of Sweden. Essays also explore craft sustainment in Finland, hand loom weaving in colonial north India, women's craft organizations in Northern Ireland and an Australian textile artist's exhibition devoted to climate change grief. Craft by LGBTQ artists from Malaysia and Canada is included. The mix of essays is topical, enlightening and intended to be provocative of the political agency of craft."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".