How to Reduce Corruption in Public Procurement: The Fundamentals
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
Procurement of goods, works and other services by public bodies alone amounts on average to between 15% and 30% of Gross Domestic Product (GDP), in some countries even more. Few activities create greater temptations or offer more opportunities for corruption than public sector procurement. Damage from corruption is estimated at normally between 10% and 25%, and in some cases as high as 40 to 50%, of the contract value.Public procurement procedures often are complex. Transparency of the processes is limited, and manipulation is hard to detect. Few people becoming aware of corruption complain publicly, since it is not their own, but government money, which is being wasted.This document is Part I of the Handbook for Curbing Corruption in Public Procurement published by Transparency International in 2006 and its purpose is to provide an overview of the problem of corruption in public contracting. Sections 2 and 3 of the Handbook, written by other authors, offer suggestions and experiences of how this problem can be addressed. The full text of the Handbook has been made available.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| 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