When Newspapers Fail to Deter Corporate Illegality: The Constraining Effects of Economic Institutions
Bibliographic record
Abstract
Abstract Social control agents aim to restrict corporate illegality, yet its prevalence highlights inconsistencies in enforcement mechanisms. To explore this issue, we examine how newspapers reduce corporate illegality by imposing ethical norms on firms. Analysing data from firms in 29 countries, we find that higher newspaper reach is only moderately associated with lower levels of corporate illegality due to key boundary conditions. Specifically, we leverage institutional anomie theory as a framework to identify and test three ways in which economic institutions constrain newspapers' ethical norm‐setting role. The negative association between newspaper reach and corporate illegality is weakened in countries with strong cultural pressure to succeed or pervasive economic penetration into newspapers. However, firm‐level shareholder orientation does not moderate this relationship. These findings highlight the importance of contextualized analyses of media landscapes and the role of economic institutions in undermining social control processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".