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Record W4360866745 · doi:10.1080/17512786.2023.2187861

Determinants of Journalists’ Trust in Public Institutions: A Macro and Micro Analysis Across 67 Countries

2023· article· en· W4360866745 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 Practice · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Influence and Politics
Canadian institutionsYork University
FundersQatar National Research Fund
KeywordsFreedom of the pressJournalismLoyaltyAutonomyPoliticsDemocracyLanguage changePolitical scienceSurvey data collectionPublic relationsWorld Values SurveyPublic trustLaw

Abstract

fetched live from OpenAlex

Scholars have repeatedly expressed concern about the societal consequences of negative media coverage toward public institutions and political actors. Yet, there remains a lack of systemic understanding about the determinants of this cynical attitude. To examine this issue, we combine aggregate data on political and economic performance with Worlds of Journalism Study (WJS) survey data on journalists’ institutional trust, watchdog and loyalty roles, editorial autonomy, professional experience, and news media ownership. Derived from interviews with 27, 657 journalists from 67 countries included in the second wave of the WJS (2012–2016), results show that democracy and press freedom are negatively correlated with journalists’ institutional trust. Quite notably, autonomous and watchdog journalists are less trusting than loyal journalists. The findings also suggest that corruption levels, annual economic growth, and type of media ownership are essential determinants in this regard.

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)0.005
metaresearch head score (Gemma)0.008
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 score0.747
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
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 head0.092
GPT teacher head0.453
Teacher spread0.361 · 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