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Record W4398788538 · doi:10.1109/mts.2024.3400033

Rossum’s Universal Robots: A Technology Studies Perspective

2024· article· en· W4398788538 on OpenAlexaff
Cameron Shelley

Bibliographic record

VenueIEEE Technology and Society Magazine · 2024
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPerspective (graphical)RobotComputer scienceArtificial intelligenceHuman–computer interactionCognitive sciencePsychology

Abstract

fetched live from OpenAlex

Karel Čapek’s play R.U.R.(Rossum’s Universal Robots)was a big hit when it was first performed in the 1920s. Written in Czech, it was soon translated into English and other languages and performed throughout Europe and the Anglo-American world [1]. It was quickly adapted for radio and television as well [2]. Through this success, it had a significant influence on technologists, writers, and general audiences [3].

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.995
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.017
Scholarly communication0.0080.011
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0100.002

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 head0.284
Teacher spread0.267 · 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.

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

Citations3
Published2024
Admission routes1
Has abstractyes

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Same venueIEEE Technology and Society MagazineSame topicHistory of Computing TechnologiesFrench-language works237,207