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Record W3122682829

Tweets and Truth: Journalism as a Discipline of Collaborative Verification

2012· article· en· W3122682829 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

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJournalismTechnical JournalismNegotiationIndividualismPublic relationsIdeologySociologyFocus (optics)JurisdictionPolitical scienceSet (abstract data type)Media studiesComputer scienceLawSocial sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines how social media is influencing the core journalistic value of verification. Through the discipline of verification, the journalist establishes jurisdiction over the ability to objectively parse reality to claim a special kind of authority and status. Social media questions the individualistic, top-down ideology of traditional journalism. The paper considers journalism practices as a set of literacies, drawing on the theoretical framework of new literacies to examine the shift from a focus on individual intelligence, where expertise and authority are located in individuals and institutions, to a focus on collective intelligence, where expertise and authority are distributed and networked. It explores how news organizations are negotiating the tensions inherent in a transition to a digital, networked media environment, considering how journalism is evolving into a tentative and iterative process, where contested accounts are examined and evaluated in public in real-time.

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)0.003
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: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.016
GPT teacher head0.326
Teacher spread0.310 · 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