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Record W4396760698 · doi:10.1080/21670811.2024.2345201

Meso News-Spaces and Beyond: News-Related Communication Occurring Between the Public and Private Domains

2024· article· en· W4396760698 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
TopicSocial Media and Politics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNews mediaPublic relationsJournalismPolitical scienceBusinessInternet privacyMedia studiesAdvertisingSociologyComputer science

Abstract

fetched live from OpenAlex

The concept of meso news-spaces refers to online spaces located between the private and public realms, where everyday users, more professional media actors, or both, can produce and share news-related content among each other, yet not to a wide audience. Such spaces are afforded by digital media platforms, including, but not limited to, Facebook groups, X spaces, and group chats on WeChat, WhatsApp, or Telegram. This special issue is devoted to further understanding news-related communication that occurs neither in fully public nor fully private realms, but between or across the two. In the introduction to the special issue, we demonstrate the significance of meso news-spaces by considering the example of the use of WhatsApp groups in the mobilization of the pro-democracy movement in Israel in 2023. We then consider the challenges that meso news-spaces pose for researchers, in terms of conceptualization, research ethics, and context. We conclude with a review of the articles of the special issue, and with directions for future research around this phenomenon, that is proving to be a significant one in the digital news environment.

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 categoriesScholarly communication
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 score0.801
Threshold uncertainty score0.998

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 studies0.0010.001
Scholarly communication0.0030.001
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 head0.028
GPT teacher head0.315
Teacher spread0.287 · 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