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The politics of global craft

2025· article· en· W7113897444 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicCrafts, Textile, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsCraftPoliticsAgency (philosophy)ExhibitionColonialismScholarshipWeavingThe arts

Abstract

fetched live from OpenAlex

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 (Bloomsbury, 2021), 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

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.740
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.254
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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