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 paper has four objectives: 1. To offer an analysis of public administration reform experiences in a set of countries chosen to illustrate the range and depth of recent administrative change. 2. To pick out from this analysis those variables that seem particularly relevant to the current condition in the Russian Federation. 3. To suggest a way of organizing thinking about a very complex and contested field. 4. To provide some pointers toward a reform strategy for policymakers in this area in the Russian Federation. Identifying the key country comparators and the relevant variables and offering a way of thinking about their significance are particularly important for the Russian Federation authorities as they prepare for implementation of the Program for the Reform of the Civil Service System in the Russian Federation. As reforms intensify, there will be a flood of serious, experienced international advisers and management experts, but there will also be those with "snake oil" to sell. Reformers need some lenses through which they can critically examine reform proposals and evaluate advice from experts. The paper draws its conclusions from an analysis of 14 countries selected by representatives of the Russian Federation government: Australia, Brazil, Canada, Chile, China, Finland, Germany, Hungary, the Netherlands, New Zealand, Poland, the Republic of Korea, the United Kingdom, and the United States. The World Bank was asked to look at a number of countries that faced similar challenges to those facing Russia in this area, while also looking at some countries that faced different problems but achieved interesting results.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it