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Record W2189174598 · doi:10.23987/sts.55240

Lessening the Evils, Online

2009· article· en· W2189174598 on OpenAlex
Annette Leibing

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

VenueScience & Technology Studies · 2009
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEmbodied cognitionNegotiationPoliticsSubject (documents)Dual (grammatical number)Public relationsInformation exchangeKnowledge managementInternet privacySociologyPolitical scienceComputer scienceWorld Wide WebSocial scienceLawArtificial intelligence

Abstract

fetched live from OpenAlex

Virtual communities are an especially rich subject for social scientists studying the dynamic and multifaceted ways that groups negotiate health-related knowledge. What are the forces shaping the health information that virtual community members circulate, evaluate and incorporate? This article explores health information circulating on an international, though mainly North American, email list for people suffering from Parkinson’s disease. The dual purpose of the list?"of support and knowledge exchange?"is shaped by a particular politics of hope, which channels knowledge and projects it into the future. This politics of hope is, at least partly, based on what I want to call “embodied molecules”?"the effectiveness of medications created by the list’s “cyberbody.” Cyberbodies, in this article, are created through the virtual community members’ embodied learning.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.699
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0030.001
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 head0.045
GPT teacher head0.357
Teacher spread0.313 · 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