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Record W3000530847 · doi:10.17351/ests2020.361

Upgraded to Obsolescence: Age Intervention in the Era of Biohacking

2020· article· en· W3000530847 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

VenueEngaging Science Technology and Society · 2020
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsTrent University
Fundersnot available
KeywordsObsolescenceFutures contractIntervention (counseling)AestheticsPsychologyHistoryPolitical scienceBusinessMedicineMarketingArtNursing

Abstract

fetched live from OpenAlex

Popularized by DIY scientists and quantified-selfers, the language of “biohacking” has become increasingly prevalent in anti-aging discourse. Presented with speculative futures of superhuman health and longevity, consumers and patients are invited to “hack” the aging process, reducing age to one of the many programs, or rather “bugs” that can be re-written, removed, and rendered obsolete. Drawing on recent examples from popular media and anti-aging promotional materials, I explore how the language of biohacking signals an orientation to the body that denies the acceptability of a body that is anything but optimal. In the endless strive towards the latest and greatest, the language of biohacking renders the old body obsolete, standing as nothing more than a relic of an outdated operating system.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.006
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.027
GPT teacher head0.303
Teacher spread0.275 · 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