Bibliographic record
Abstract
This paper examines the persistence of corrupt practices within organizations despite increasing expenses on compliance policies, systems, and measures. Formal control systems designed to prevent unethical and illegal behavior have become a widespread practice. However, research suggests that costly, sophisticated anti-corruption strategies have not been achieving their desired outcomes. From a theoretical stance, different perspectives and bodies of literature have been brought forward to understand organizational corruption as a systemic and synergistic phenomenon. Nonetheless, research on the integration between antecedents, processes, and consequences of organizational corruption remains limited. This study critically reviews knowledge on normalized organizational corruption by integrating extant literature on the antecedents and processes of organizational corruption and on organizational response to corruption. As a result, I introduce a number of research questions, whose answers might lead to the development of a theory of organizational corruption persistence, with relevant implications for organizational practice and policy making.
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 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 | 0.025 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.024 | 0.038 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".