Foreign Approac hes to the Audit of Transport System Efficiency at the Regional Level
Bibliographic record
Abstract
The article is devoted to consideration of foreign instruments for performance audit in the transport sector and to assessment of possibility of applying the methods and procedures of performance audit by Russian regional control and accounting bodies. The objective of the study is to comprehensively analyse the international experience of regulation and organisation of performance audit in the transport sector based on the practices of the Auditor General of Scotland (Great Britain) and the Auditor General of Manitoba (Canada). Considering the traditionally high share of regional budget expenditures spent on development of the transport system, it is noted that assessment of the economy, productivity and efficiency of the use of public resources is important not only for regional authorities, but also for the population and business entities. Based on the analysis of the best practices of regional government audit bodies of Great Britain and Canada in terms of performance audits in the transport sector, advanced methods and audit procedures were recorded that can be applied by Russian regional control and accounting bodies. In particular, the specifics and accuracy of recommendations to the executive authorities presented in the audit report; procedure of assessing correctness of tender procedures and effectiveness of contract execution as part of the performance audit; wide use of external experts during inspections and other features have been noted.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".