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Record W2596864168 · doi:10.1109/mts.2017.2670224

Exoskeletons, Transhumanism, and Culture: Performing Superhuman Feats

2017· article· en· W2596864168 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Technology and Society Magazine · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsOntario Tech University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTranshumanismFraming (construction)Rhetorical questionRhetoricSociologyContext (archaeology)PoliticsConversationDystopiaAestheticsTechnological convergencePopular cultureMilitarizationMedia studiesEnvironmental ethicsPolitical scienceLawEngineeringHistoryPhilosophy

Abstract

fetched live from OpenAlex

In this article we study how exoskeletons are construed through three dominant but interrelated presentations: 1) popular science journalism, 2) advertisements of military innovation, and 3) blockbuster science fiction film. We address how these media function to alter attitudes about the future. The attitudinal framing of the exoskeleton asks that people aspire to transhumanism, and that they “imagine the possibilities in the near future of dramatically enhance[ed) human mental and physical capacities” [4). In this case, they are being encouraged to visualize a militarized future. More so, the rhetorical proposition calls upon people to identify personally with the technology. The rhetoric conveys a militarized identity through celebration, anticipation, and to an extent, panic. It unites excitement and fear through entertainment, but it also succeeds in distorting the conversation of what exoskeleton technology would actually mean in a nonfictional, socio-political, or military context. Michael, Fusco, and Michael [5) identify the “socio-ethics” concerning emerging inventions, as “the moral principles which govern a particular society at large.” We seek in our work to disclose some of the socio-ethical cultural manipulation conveyed through popular channels concerning exoskeletons.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.318
Teacher spread0.272 · 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