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Beyond Prosthetic Memory

2018· article· en· W4301134914 on OpenAlexfundno aff
Amelia DeFalco

Bibliographic record

VenueAge Culture Humanities An Interdisciplinary Journal · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
FundersUniversity of TorontoUniversity of LeedsOhio State UniversityOhio State University Press
KeywordsPosthumanEmbodied cognitionExceptionalismAestheticsPosthumanismSociologyPerspective (graphical)IllusionPsychologyEpistemologyArtPolitical scienceLawPhilosophyVisual artsCognitive psychology

Abstract

fetched live from OpenAlex

Literary and cinematic speculations about the future of care, read in tandem with the rising prominence of actual robotic caregivers, foretell a future in which human interaction is no longer an inevitable feature of care relations. This essay considers the social, cultural and ethical implications of robotic care alongside a particular speculative representation of posthuman care, the 2012 film Robot and Frank. The film demonstrates how the intimacy of human/machine care relationships can supply posthumanist insights into the illusion of human invulnerability and exceptionalism that obscure the heterogeneity of embedded and embodied subjects. Not only does the film dramatize the fundamental anxieties caregiving robots incite, it also offers provocative posthumanist critiques of human exceptionalism, conjuring haptic affects that trespass the boundaries between humans and machines.

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)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.010
Scholarly communication0.0100.011
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0420.007

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 head0.038
GPT teacher head0.292
Teacher spread0.254 · 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
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

Citations5
Published2018
Admission routes1
Has abstractyes

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