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Record W2319907945 · doi:10.1177/0270467612459924

“Obligatory Technologies”

2012· article· en· W2319907945 on OpenAlexaff
Jennifer A. Chandler

Bibliographic record

VenueBulletin of Science Technology & Society · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTechnological determinismEmerging technologiesAutonomyFatalismDeterminismTechnological changeIdeologyCompetition (biology)SociologyPolitical scienceEpistemologySocial scienceLawEconomicsPoliticsComputer science

Abstract

fetched live from OpenAlex

The ideas of technological determinism and the autonomy of technology are long-standing and widespread. This article explores why the use of certain technologies is perceived to be obligatory, thus fueling the fatalism of technological determinism and undermining our sense of freedom vis-à-vis the use of technologies. Three main mechanisms that might explain “obligatory technologies” (technologies that must be adopted) are explored. First, competition between individuals or groups drives the adoption of technologies that enhance or extend human capacities. Second, individuals and groups may become dependent on technologies. Third, technologies induce changes in social norms and values that may come to be enforced through various social mechanisms, including the law. The widespread ideology of the beneficence and inevitability of technological progress in our culture helps this process along.

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)0.010
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.997
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.031
Scholarly communication0.0070.010
Open science0.0010.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.002

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 head0.045
GPT teacher head0.313
Teacher spread0.268 · 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.

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

Citations19
Published2012
Admission routes1
Has abstractyes

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