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Accountability Journalism and Corporate Illegality: An Application of Institutional Anomie Theory

2023· article· en· W4385225084 on OpenAlexaff
Tony Jaehyun Choi, Kam Phung

Bibliographic record

VenueAcademy of Management Proceedings · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Influence and Politics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNewspaperAnomieAccountabilityCorporate governanceJournalismWrongdoingShareholderInstitutional theoryPublic relationsPolitical economyPolitical scienceBusinessSociologyAdvertisingLawSocial scienceFinance

Abstract

fetched live from OpenAlex

Research on the watchdog role of newspapers mainly analyzes the relationship between firm coverage by major newspapers and target firms’ engagement in wrongdoing or negative repercussions. Yet, the dwindling presence of newspapers amidst the past two decades illuminates a distinct need to examine differences observed in the macro-level media landscape. To this end, we advance research on the institutional determinants of corporate illegality by drawing on institutional anomie theory which highlights the role of non-economic institutions in balancing out excessive economic influences on illegality. Applying the key arguments of the theory to the behavior of firms from 29 countries, we first find that firms headquartered in countries with higher newspaper reach are less likely to engage in corporate illegality. Yet, such a pattern is less pronounced when a country is characterized by strong cultural pressure to succeed or the penetration of economic influences into newspapers. Firm-level shareholder orientation, however, did not mitigate the negative association between newspaper reach and illegality. Based on these results, we discuss the importance of analyzing macro-level media landscapes and related institutional conditions that compromise newspapers as social control agents.

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 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 score0.434
Threshold uncertainty score0.277

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.069
GPT teacher head0.354
Teacher spread0.284 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2023
Admission routes1
Has abstractyes

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