Revisiting informal payments in 29 transitional countries: The scale and socio-economic correlates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it