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La Grosbotique

2018· article· fr· W2330521179 on OpenAlexaff
Stéphanie Walsh Matthews

Bibliographic record

VenueInterfaces numériques · 2018
Typearticle
Languagefr
FieldArts and Humanities
TopicPhilosophical and Theoretical Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Dans l’espoir de concevoir un être qui n’en est pas un, le robot-humanoïde ressemble tout de même à celui qui l’a créé. La trace humaine guide tout le processus de création et, par la suite, marquera toutes ses interactions. Paradoxalement, il n’y a rien d’humain – outre peut-être l’esquisse de la forme – car le robot-humanoïde est une machine dont les fonctionnements sont régis et manipulés à l’aide de programmes, d’interactions digitales et de mémoires artificielles. C’est l’antithèse de ses parties qui fait du robot-humanoïde l’être contemporain le mieux situé à porter l’étiquette du grotesque. Nous proposons de nous engager dans une évaluation du rapport avec le robot à l’aide d’une approche anthropologique et sémiotique.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.010
Scholarly communication0.0080.006
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0450.012

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 head0.017
GPT teacher head0.266
Teacher spread0.249 · 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 designTheoretical or conceptual
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

Citations0
Published2018
Admission routes1
Has abstractyes

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