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Record W7023258493

Touches

2017· other· en· W7023258493 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of the Arts London Research Online (University of the Arts London) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSanitationMegacityGarbageResidenceMetisAssemblage (archaeology)Work (physics)
DOInot available

Abstract

fetched live from OpenAlex

Artist Mierle Laderman Ukeles has made it her life’s work to dignify and celebrate the often unseen and disregarded work of maintenance workers; the men and women who keep megacities such as New York running. The official, but unpaid, artist in residence of the New York Sanitation department she spent almost a year between 1979 and 1980 shaking the hand of over 8500 sanitation workers, telling them ‘Thank you for keeping New York alive’. \n \nUkeles work has only recently found the appreciative audience and respect in deserves with Queens museum in New York staging a retrospective of her work, complete with mirrored garbage truck and LED lit map of her route around New York. \n \nWriter and artist Andrea Mason pays homage to Ukeles with her own piece TOUCHES, of which she says: \n \n‘These reverbing 8,500 “touches”, unknowable yet human, bring to mind the social ecology of urban living, at once necessary and a challenge, as well as celebrating the nature of community, and the notion that the key to a city’s sustainability and transformability lies in the endurance of its communities. \n \nTouches is extracted from a longer work-in-progress, a Fluxus novel about waste; an assemblage piece which utilises inventory, micro fiction, diary entry, haikuesque prose poetry, and concrete prose, which investigates the daily systems of life and the body, as well as societal systems and the entropy, or waste, therein.’ \n \nKathleen McCaul \n \nMega City Fictions is a project by Kathleen McCaul, funded by the CHASE Doctoral Training Partnership, and produced in collaboration with UEA's Boiler House Press. \n \nMegacity Fictions aims to investigate how writers and artists are responding to vast cityscapes which mutate and spread at unparalleled rates, often displaying extremes of global wealth and poverty; vertical towers built on new economic wealth surrounded by sprawls of immigrant slums. Submissions in creative non-fiction, fiction, ficto-critical writing, photography and digital art that explore particular megacities, and the concept of massive urban hubs in general, are all invited.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.528
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0090.006
Open science0.0010.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.5280.271

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 head0.063
GPT teacher head0.298
Teacher spread0.235 · 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 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
Published2017
Admission routes1
Has abstractyes

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