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Record W4387935433 · doi:10.11647/obp.0363.10

10. HE4Good assemblages

2023· book-chapter· en· W4387935433 on OpenAlexaff
Frances Bell, Lorna M. Campbell, Giulia Forsythe, Lou Mycroft, Anne-Marie Scott

Bibliographic record

VenueOpen Book Publishers · 2023
Typebook-chapter
Languageen
FieldArts and Humanities
TopicArt, Technology, and Culture
Canadian institutionsBrock University
Fundersnot available
KeywordsQuiltPosthumanQuiltingSociologyPraxisFeminismEconomic JusticeAestheticsPedagogyVisual artsGender studiesArtEpistemologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

FemEdtech is a reflexive, emergent network of people learning, practising and researching in educational technology converging on the intersections of feminism, education, and technology. The FemEdTech Quilt of Care and Justice in Open Education was a collaborative quilting project emerging from the FemEdTech network. Through a posthuman lens, this chapter explores the lives and purposes of the FemEdTech Quilt assemblage, using makers’ stories of their quilt squares, images, and Markov chain poetry, alongside ‘unseen’ contributions such as the thoughts, feelings, readings, and memories articulated within a slow ontology of feminist praxis, that authors shared during Thinking Environment conversations.

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)0.002
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.182
Threshold uncertainty score0.610

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.006
Scholarly communication0.0090.008
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.1820.049

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 head0.054
GPT teacher head0.245
Teacher spread0.191 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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