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Record W3023457246 · doi:10.1177/1464884920915372

Studying incidental news: Antecedents, dynamics and implications

2020· article· en· W3023457246 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

VenueJournalism · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhenomenonDynamics (music)News mediaAffordancePoliticsResistance (ecology)Focus (optics)Consumption (sociology)News valuesPsychologyMotivated reasoningCognitionSocial psychologyPolitical scienceSociologyEpistemologyCognitive psychologyMedia studiesSocial scienceEcology

Abstract

fetched live from OpenAlex

In light of concerns about decreasing news use, a decline in interest in political news or even active avoidance or resistance of news in general, the idea of ‘incidental news’ has been seen as a possible remedy. Generally, ‘incidental news’ refers to the ways in which people encounter information about current events through media when they were not actively seeking the news. However, scholars studying incidental news through different theoretical and methodological perspectives have been arriving at differing evaluations of the significance and implications of this phenomenon – to the extent of downright contradictory findings. This introductory piece posits the aim of this special issue on Studying Incidental News: a conceptual clarification of incidental news exposure. In this issue, scholars coming from different approaches, ranging from cognitive processing, ecological models, emergent practices and a focus on platform affordances, show how different theoretical perspectives help account for various dimensions of incidental news consumption, and thus help explain the often conflicting findings that have been suggested so far.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.052
GPT teacher head0.360
Teacher spread0.308 · 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