Revisiting informal payments in 29 transitional countries: The scale and socio-economic correlates
Bibliographic record
Abstract
This study assesses informal payments (IPs) in 29 transitional countries using a fully comparable household survey. The countries of the former Soviet Union, especially those in the Caucasus and Central Asia, exhibit the highest scale of IPs, followed by Southern Europe, and then Eastern Europe. The lowest and the highest scale of IPs were in Slovenia (2.7%) and Azerbaijan (73.9%) respectively. We found that being from a wealthier household, experiencing lower quality of healthcare in the form of long waiting times, lack of medicines, absence of personnel, and disrespectful treatment, and having relatives to help when needed, are associated with a higher odds ratio of IPs. Conversely, working for the government is associated with a lower odds ratio of IPs. Living in the countries of the former Soviet Union and in Mongolia is associated with the highest likelihood of IPs, and this is followed by the countries of the Southern Europe. In contrast, living in the countries of Eastern Europe is associated with the lowest likelihood of IPs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".