The Use of Key Performance Indicators for the FAS: Analysis Based on the Statistics of Adjudications
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Bibliographic record
Abstract
Outcomes of the key performance indicators application for the assessment of the public authority performance are ambiguous. Theory of incentive contracts as well as international experience highlight difficulties and possible externalities of KPI setting for the public authority. The motivation system often distorts incentives of the public authorities, and the applied indicators do not correctly reflect the priorities of enforcement for the society. One specific example is the assessment of performance of the Russian competition authority. In the paper we analyze the peculiarities of formation of the ratio of infringement decisions that have come into legal force to all infringement decisions made by the competition authorities applied as one of the key performance indicators. Using the data of the database of judicial reviews of infringement decisions, we show that the assessment of FAS performance based on the share of infringement decisions that have come into legal force, distorts incentives of the authority substantially. It motivates the competition authority for making a large number of infringement decisions with a low probability to reverse but with a low positive impact on consumer surplus and total welfare.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| 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