Bibliographic record
Abstract
Purpose The purpose of this paper is to see to what extent ethical relativism could be adopted as justification for corrupt practices. Design/methodology/approach The paper analyzed the various perspectives which were used to define the boundaries of corruption: a structural perspective, a social‐normative perspective, and an organizational‐normative perspective. It then identified the various ethics positions that could be chosen and particularly focuses on ethical relativism. Findings The paper finds that corruption should be considered not only as a social construct, a cultural phenomenon (from a social‐historical viewpoint), but also as an object for ethical reasoning (from a moral viewpoint). Owing to that fact that corruption serves both to sway people away from their moral duties and to favour self‐interest, we cannot look at corruption as if it would only be a cultural phenomenon. Originality/value The paper presents the case of guanxi networks as a cultural phenomenon that is not rooted in Confucian traditional texts, but that makes an integral part of the present Chinese culture. The distorted meaning of guanxi (as favoritism) should make everybody more cautious about the risk to undertake unethical actions.
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 | 0.023 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.055 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| 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".