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Record W2012995914 · doi:10.1177/0196859906294840

Internet Web Logs as Cultural Resistance: A Study of the SARS Arts Project

2006· article· en· W2012995914 on OpenAlexaff
James Gillett

Bibliographic record

VenueJournal of Communication Inquiry · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsThe InternetCONTESTResistance (ecology)Opposition (politics)PoliticsThe artsSociologyPolitical sciencePublic relationsMedia studiesWorld Wide WebLaw

Abstract

fetched live from OpenAlex

This article examines an Internet project — sarsart.org — that features digital artworks created in response to the severe acute respiratory syndrome (SARS) outbreak in spring 2003. Qualitative methods including archival research, semiotic analysis, and interviews are used to examine the emergence and substance of this Internet project. The analysis identifies ways in which contributions by artists and bloggers (i.e., individuals with their own Internet site or Web log) contest institutional representations of SARS. The site challenges the representation of the outbreak on three levels: portrayals of citizens affected by SARS, portrayals of health professionals, and portrayals of the risk and panic associated with the outbreak. The argument is made that Internet projects such as sarsart.org can increase the capacity for cultural resistance by creating greater opportunities for the expression of political opposition to institutional authority.

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)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0160.014
Scholarly communication0.0100.007
Open science0.0020.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.151
GPT teacher head0.343
Teacher spread0.192 · 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 designQualitative
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

Citations35
Published2006
Admission routes1
Has abstractyes

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