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Record W4307850665 · doi:10.33182/joph.v2i3.1649

Autonomy, Posthuman Care, and Romantic Human-Android Relationships in Cassandra Rose Clarke’s The Mad Scientist’s Daughter

2022· article· en· W4307850665 on OpenAlexaff
Monica Sousa

Bibliographic record

VenueJournal of Posthumanism · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsYork University
Fundersnot available
KeywordsPosthumanHumanityFeelingAutonomyDaughterRomancePsychoanalysisPosthumanismAndroid (operating system)AestheticsSociologyPsychologyArtPhilosophySocial psychologyLawComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This essay looks at the representations of romantic relationships between humans and intelligent androids in Cassandra Rose Clarke’s science fiction novel, The Mad Scientist’s Daughter (2013). Clarke’s novel encourages readers to re-evaluate common fears surrounding human-interaction. By closely looking at this novel, this essay offers a posthuman care-ethical approach. This essay argues that in depictions of romances between humans and androids, posthuman intimacies can reaffirm a humanity that is shaped by care when attention is given to autonomy. This care ethic suggests a posthumanist vision of humanity that requires trying to understand and be willing to learn more about the feelings and choices of a nonhuman being – even if those feelings and choices are artificially simulated.

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)0.003
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 score0.008
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.041
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.067
GPT teacher head0.319
Teacher spread0.252 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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