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Record W2044104972 · doi:10.5931/djim.v10i1.3355

Doctor Who in an Exciting Adventure with the Information Society: Fears and Doubts of Technological Utopia in Selected Serials of the Original Series

2014· article· en· W2044104972 on OpenAlexaffvenue
James David Ross

Bibliographic record

VenueDalhousie Journal of Interdisciplinary Management · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace Science and Extraterrestrial Life
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTechnocracyAdventureUtopiaDystopiaSpace (punctuation)Media studiesSociologySocial sciencePolitical scienceHistoryLawComputer scienceArt historyPolitics

Abstract

fetched live from OpenAlex

Science fiction is a genre uniquely suited to considering the implications of technological developments. The long-running BBC series Doctor Who, by nature of its longevity, presents the opportunity to investigate evolving attitudes towards emerging information technology. This paper analyzes three serials from the original run of Doctor Who and traces the development in the show's portrayal of the future of information technology (IT) from 1967 to 1975. I argue that early portrayals of futuristic information societies, in serials such as “The Wheel in Space” and “The Seeds of Death,” take a mainframe-oriented view of IT's future and present a centralized, technocratic conception of the governments of the future. I conclude that the 1976 serial “The Deadly Assassin” dramatically reverses these earlier portrayals, demonstrating a perceptive awareness of the dawning of the microcomputer revolution and presenting a cynical take on the potential of technological advancement to lead to technocratic utopia.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.245
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2014
Admission routes2
Has abstractyes

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