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Record W4200578067 · doi:10.1111/jola.12339

Securitizing Communication: On the Indeterminacy of Participant Roles in Online Journalism

2021· article· en· W4200578067 on OpenAlexaff
Francis Cody, Alejandro I. Paz

Bibliographic record

VenueJournal of Linguistic Anthropology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsJournalismIndeterminacy (philosophy)Social mediaSecuritizationRepresentation (politics)PoliticsSociologyMedia studiesNews mediaPublic relationsPolitical scienceLawEpistemologyBusiness

Abstract

fetched live from OpenAlex

This article takes Judith T. Irvine’s insights about the indeterminacy of participant roles and interpretive frameworks to explore how the increased use of social media in journalism leads to new quandaries for political actors. The dialogics of distributing or amalgamating participant roles provide for a particularly tricky domain of maneuver for journalists in India and Israel, where rightwing leaders seek to control news that disseminates rapidly on the currents of social media. Journalists have long sought to avoid becoming the story themselves, as part of claiming liberal positions that distinguish the reported events from their representation. It considers the current attempt to clamp‐down on social media use by journalists as a securitization of communication, where the very journalistic utterance is used by ruling politicians to make the journalist, or potentially the news media more generally, into a threat to public security. However, even such policing can be too slow. This article thus also considers how outraged publics become an important aspect of policing social media.

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)0.059
metaresearch head score (Gemma)0.083
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.312

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.083
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0120.101
Scholarly communication0.0220.038
Open science0.0030.016
Research integrity0.0060.007
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 head0.103
GPT teacher head0.419
Teacher spread0.317 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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