Bibliographic record
Abstract
Abstract Political theorists are aware that the old-fashioned model of state power, according to which elected officials make policy decisions, which are then faithfully enacted by a loyal cadre of public servants, is hopelessly outdated. The complexity of the modern state, not to mention the difficulty of the economic and social problems it confronts, is such that a great deal of rule-making power is delegated to public servants. Yet if public servants are not merely in the business of administration, but are also deciding questions of policy, how are they making these decisions, and what normative principles inform their judgments? The Machinery of Government attempts to answer this question. The central challenge involves reconciling the tension between the traditional commitment to political neutrality on the part of the civil service with the fact that administrative discretion inevitably involves making normative judgments. State employees are in many cases unable to do their jobs effectively without some conception of where the public interest lies. It seems inevitable that this will conflict with the commitment to political neutrality, since this conception of the public interest may be tension with that of elected officials. The solution to the dilemma lies in an understanding of the constraints that liberalism imposes on popular sovereignty in a liberal-democratic polity. Not only do courts play an important role in checking the power of democratic publics, the executive branch is also the custodian of certain fundamental liberal principles.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".