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Record W7117241621 · doi:10.1163/23644583-12340001

The Life of Droids: A Droidean Corporeal Horror

2025· article· en· W7117241621 on OpenAlexaff
Andrew Gibbons, Andrew Denton, Rainie Fengyi Yu

Bibliographic record

VenueVideo Journal of Education and Pedagogy · 2025
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Philosophy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsUncannyExhibitionWeavingUncanny valleyWork (physics)

Abstract

fetched live from OpenAlex

Abstract In this article the life of droids is explored through a weaving of scenes, dialogue, analysis, theory and an exhibition. The imagery and text are employed to work through the experiences of the droids and the relationships that are revealed, or perhaps even presenced (Heidegger, 1993). The works of Heidegger and Camus on technology and science, the story of Viktor Frankenstein’s absence of care for ‘his’ creation, and insights from Daniel Wallace’s book, Star Wars: The New Essential Guide to Droids add textual flavour to the images that have been produced by the authors and that invite exploration of life in the age of droidean corporeal horror. In this exhibition of machine lives, the images are presented as uncanny moments (Rancière, 2010), revealing questions concerning technology and being (Heidegger, 1993). The educational intention of this work is not to emancipate machine life through the horror stories of droidean cultures and communities, but rather to offer insights into the error of Modern mastery.

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 score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.024
Scholarly communication0.0070.005
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.015
GPT teacher head0.316
Teacher spread0.301 · 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
Published2025
Admission routes1
Has abstractyes

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