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Record W2586681190 · doi:10.1177/0725513616689389

Replies

2017· article· en· W2586681190 on OpenAlexaff
Andrew Feenberg

Bibliographic record

VenueThesis Eleven · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsReactionaryCriticismHumanismValue (mathematics)EpistemologyState (computer science)SociologyCritical theoryAestheticsLaw and economicsPhilosophyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

In these replies I address criticism of my work on the grounds that I adopt a ‘humanist’ approach, underestimate the aesthetic potential of contemporary video games, overlook the role of the nation-state in resisting technological imperialism, fail to appreciate the risks of reactionary appropriations of technology, and introduce an extrinsic and dubious aesthetic value into the philosophy of technology. In the course of responding to these criticisms, I reiterate several of the basic claims of critical theory of technology.

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)0.005
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.096
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0050.003
Open science0.0020.004
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0960.055

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 head0.049
GPT teacher head0.334
Teacher spread0.284 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2017
Admission routes1
Has abstractyes

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