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Record W1969457880 · doi:10.1086/523289

Technology/Ideology: How Ideological Fields Influence Consumers' Technology Narratives

2007· article· en· W1969457880 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Consumer Research · 2007
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsYork University
Fundersnot available
KeywordsIdeologyArticulation (sociology)NarrativeSemioticsField (mathematics)SociologySemantic fieldSystematic ideologyEpistemologyLinguisticsPolitical sciencePoliticsPhilosophyLaw

Abstract

fetched live from OpenAlex

Abstract Through a systematic study of consumer narratives, this article models how technology ideologies influence consumer-level thought, speech, and action. Applying critical discourse analysis and articulation theory approaches, a semiotic square model represents the relations between Techtopian, Green Luddite, Work Machine, and Techspressive ideological elements in an ideological field. The narratives of individual consumers move between ideological elements in ways suggested by the model's semantic relations. The results reveal novel aspects of consumers' dynamic relations to technology ideology and invite further investigations of technology and consumption ideology.

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)0.004
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.002
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 head0.052
GPT teacher head0.386
Teacher spread0.334 · 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