MétaCan
Menu
Back to cohort
Record W2026967522 · doi:10.1177/0270467609355051

Control Yourself, or at Least Your Core Self

2010· article· en· W2026967522 on OpenAlexaff
Lisa M. Austin

Bibliographic record

VenueBulletin of Science Technology & Society · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsParallelsIntrospectionControl (management)Core (optical fiber)Internet privacyPhilosophy of technologyRoot (linguistics)Emerging technologiesEpistemologySociologyComputer scienceEngineeringPhilosophyPhilosophy of scienceArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

Contemporary privacy debates regarding new technologies often define privacy in terms of control over personal information such that the privacy “problem” is a lack of control and the privacy “solution” is increased control. This article questions the control-paradigm by pointing to its parallels with earlier debates in the philosophy of technology regarding technology that was out-of-control. What first-generation philosophers of technology understood was that at the root of the questioning of technology lay a need to question the modern self itself. Legal debates regarding privacy renew the importance of this question, for the control-paradigm perpetuates a view of the self as an individual with an inner core transparent to itself on solitary introspection and revealed to others through self-conscious acts of disclosure. Increasingly, this model fails to account for the challenges raised by new technologies and calls for rethinking.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.018
Scholarly communication0.0060.008
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.002

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 head0.050
GPT teacher head0.324
Teacher spread0.274 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueBulletin of Science Technology & SocietySame topicNeuroethics, Human Enhancement, Biomedical InnovationsFrench-language works237,207