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Record W3111082479 · doi:10.1111/plar.12380

When All That Is Solid Does Not Melt into Air: Labor, Politics and Materiality in a Bosnian Detergent Factory

2020· article· en· W3111082479 on OpenAlexaff
Larisa Kurtović

Bibliographic record

VenuePoLAR Political and Legal Anthropology Review · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFactory (object-oriented programming)Materiality (auditing)PoliticsFutures contractEthnographyVictorySociologyValue (mathematics)Political scienceAestheticsLawEconomicsArtAnthropology

Abstract

fetched live from OpenAlex

Abstract Can futures be assembled out of ruins? This article engages this question through an ethnographic account of a workers’ struggle in northeastern Bosnia‐Herzegovina to restart production in a bankrupted factory almost destroyed by privatization. From 2011 through 2015, workers of Dita organized to challenge liquidation of the factory assets. Their struggle resulted in an unprecedented victory when production was restarted in 2015 and the factory reprivatized in 2017. Workers had to carry out their struggle amidst two opposing pulls: the need to draw attention to the processes of destruction that formed part of postwar privatization, and to simultaneously argue for the factory's continued value and viability. The analysis explores the openings and risks created by the ongoing anthropological debates on the centrality of matter—and especially ruins—to social life at large. It argues that where we locate potential and how we name embattled matter is not merely a theoretical but also a political question.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.030
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.119
GPT teacher head0.319
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations9
Published2020
Admission routes1
Has abstractyes

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