Bibliographic record
Abstract
Citizens have lost trust in their institutions of public governance. In trying to fix the problem, presidents and prime ministers have misdiagnosed the patient, failing to recognize that government bureaucracies are inseparable from political institutions. As a result, career officials have become adroit at managing the blame game but much less so at embracing change. Donald Savoie looks to the United States, Great Britain, France, and Canada to assess two of the most important challenges confronting governments throughout the Western world: the concentration of political power and the changing role of government bureaucracy. The four countries have distinct institutions shaped by distinct histories, but what they have in common is a professional non-partisan civil service. When presidents and prime ministers decide to expand their personal authority, national institutions must adjust while bureaucracies grow to fill the gap, paradoxically further constricting government efficacy. The side effects are universal – political power is increasingly centralized; Parliament, Congress, and the National Assembly have been weakened; Cabinet has lost standing; political parties have been debased; and civil services have been knocked off their moorings. Reduced responsibility and increased transparency make civil servants slow to take risks and politicians quick to point fingers. Government astutely diagnoses the problem of declining trust in government: presidents and prime ministers have failed to see that efficacy in government is tied to well-performing institutions.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.183 | 0.089 |
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".