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Record W2028324122 · doi:10.1353/sls.0.0043

Science, Technologies, and Deafness: An Introduction to Organized Knowledge as Social Problem

2010· article· en· W2028324122 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSign language studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsWitnessSign languageSign (mathematics)Emerging technologiesSociologyLibrary scienceEngineering ethicsPolitical scienceComputer scienceLinguisticsEngineeringLaw

Abstract

fetched live from OpenAlex

The introduction to this volume connects the burgeoning academic field of science and technology studies (STS) with studies into the technologies of deafness; examples of such technologies include genomics, cochlear implantation, sign language corpora, educational tracking systems, and mobile communications. The subsequent articles all bear witness to the extensive interweaving of advanced technologies, scientific knowledge, deafness and sign language. The papers brought together in this special issue were presented at two prominent international conferences: the annual meeting called “Ways of Knowing” held by the Society for Social Studies of Science (4S), in Montreal from October 11–13, 2007; and the annual meeting called “Acting with Science, Technology and Medicine,” held jointly by 4S and the European Association for the Study of Science and Technology (EASST) in Rotterdam from August 20–23, 2008.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.390
Teacher spread0.372 · 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