Bibliographic record
Abstract
The paper is divided in three sections. In the first section, I question the use of the statist redistributive paradigm in federalism. In the second section, I argue that efficiency is a moral principle and that it has a strong normative appeal, especially in contexts of diversity. I show that adopting efficiency as a guiding principle to think of the role of the state, especially in contexts of pluralism, as in MNF, allows us to consider the division of competences in a way that is yet unexplored in political philosophy. Furthermore, I argue that embracing efficiency allows us to avoid the moral problems that other moral approaches encounter, especially as I will defend a non-utilitarian conception of efficiency. That also allows me to show that if one opts for the view that pictures federalism as an efficiency maximizing enterprise, it does not lead to a libertarian conception of federalism. Finally, I try to briefly sketch a possible connection between the principle of efficiency and republican ideal of ‘non-domination’ (Pettit 2012). More specifically I suggest that the pursuit of ‘non-domination’ is totally compatible with the pursuit of efficiency in MNF. In other words, the federal government can interfere to resolve government failures at the sub-unit level, for instance externalities, without being or becoming a dominating agent. The ideal of non-domination supports the sort of strong government interventions defended by egalitarians without having to compromise on the autonomy of federated entities. The combination of efficiency and non-domination ends with a defense of asymmetrical federal arrangements, without sacrificing the equality that states ought to preserve.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".