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Record W4403981346 · doi:10.33621/jdsr.v6i3.33328

"Don't be too proud of this technological terror you've constructed"

2024· article· en· W4403981346 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.

Bibliographic record

VenueJournal of Digital Social Research · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsUniversity of WaterlooBishop's University
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Transhumanism is a school of thought that promotes the enhancement of humanity through technological intervention (e.g., cloning, gene therapies, uploading one’s mind to a computer, nanotechnology). Due to its aims of altering evolutionary processes (Bostrom, 2005), transhumanism is highly controversial (Sinicki, 2015). The ideology finds support from younger men, as well as those engaged in science-fiction literature (Gangadharbatla, 2020; Koverola et al., 2022). The present study aimed to investigate the role of gender and specific science fiction fan identities as predictors of transhumanism in three different samples of fandoms affiliated with science-fiction (e.g., anime fans, furries, and Star Wars fans) as well as in a control sample of college students. Participants (N = 6840) responded to a novel measure of transhumanist orientation in either an online or in-person survey. The findings indicated that men were the most likely to endorse transhumanism, as were fans of Star Wars and furries. Overall, the present study supports theorizing that transhumanism may be an influential motif in the science-fiction genre, as well as an appealing ideology for men.

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)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
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 score0.155
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.288
GPT teacher head0.470
Teacher spread0.182 · 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