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Record W4392241844 · doi:10.1080/21670811.2024.2320249

The Threat of Misinformation on Journalism’s Epistemology: Exploring the Gap between Journalist’s and Audience’s Expectations when Facing Fake Content

2024· article· en· W4392241844 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

VenueDigital Journalism · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsMisinformationJournalismFake newsContent (measure theory)Political scienceDisinformationSociologyCrisis communicationPublic relationsMedia studiesPsychologyInternet privacySocial mediaComputer scienceLaw

Abstract

fetched live from OpenAlex

This study analyzes the discourse of reporters, editors and audiences in focus groups and in-depth interviews, examining the expectations on journalists when facing misinformation. While both groups agree that journalistic information is critical, how this expectation is met varies. On the one hand, the audience’s way of knowing involves diverse assessments regarding valuable information; also, they are dubious about journalists’ intentions. On the other hand, journalists exhibit a limited understanding of the audience’s informational needs and encounter practical challenges in rigorously fact-checking, affecting their authority in knowledge generation. The study proposes a discussion on acknowledging their complex epistemologies to benefit mutual understanding. Doing this can establish structural support for journalistic information, contributing to trust in journalism when challenged by sources spreading misinformation.

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, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
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
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0030.003
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 head0.181
GPT teacher head0.338
Teacher spread0.157 · 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