The proliferation of neoliberal ideology: A study of international anti-corruption discourse through the lens of institutional entrepreneurship theory
Bibliographic record
Abstract
This study examines the development and influence of the international anti-corruption regime, utilizing Critical Discourse Analysis (CDA) to dissect the discursive practices that shape perceptions of corruption and the strategies employed to combat it. Our analysis reveals how Western institutional entrepreneurs play a pivotal role in defining corruption predominantly as bribery and governance failures, underpinned by a neoliberal ideology that prescribes societal norms and identifies corrupt practices. By exploring the mechanisms through which this ideology is propagated, the research enriches institutional entrepreneurship theory and highlights the neoliberal foundations of current anti-corruption efforts. This study not only enhances our understanding of the institutional frameworks that govern anti-corruption discourse but also demonstrates how discourse legitimizes certain ideologies while marginalizing others. The findings offer practical tools for altering power dynamics, promoting equitable participation, and addressing the imbalanced North-South power relations. By challenging established perspectives, this research contributes to transformative discourse and action, offering new pathways for understanding and combating corruption. These insights have significant theoretical and practical implications for improving the effectiveness of corruption prevention and counteraction strategies globally.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.045 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".