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Record W3125285252 · doi:10.1017/s0003055407070268

Federalism, Liberalism, and the Separation of Loyalties

2007· article· en· W3125285252 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Political Science Review · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsFederalismPoliticsPolitical scienceLoyaltyLiberalismDual federalismSeparation of powersLaw and economicsTiebout modelPolitical economyDemocracySociologyLawEconomicsNeoclassical economics

Abstract

fetched live from OpenAlex

Federalism, when it has not been ignored altogether in normative political theory, has typically been analyzed in terms that fail to match the institution as it exists in the world. Federations are made up of provinces that are too few, too large, too rigid, too constitutionally entrenched, and too tied to ethnocultural identity to match theories based on competitive federalism, Tiebout sorting, democratic self-government, or subsidiarity. A relatively neglected tradition in liberal thought, based on a separation of loyalties and identifiable in Montesquieu, Publius, Constant, Tocqueville, and Acton, however, holds more promise. If the purpose of federalism is to compensate for worrisome tendencies toward centralization, then it is desirable that the provinces large enough to have political power be stable and entrenched and be able to engender loyalty from their citizens, such as the loyalty felt to ethnoculturally specific provinces. Separation of loyalty theories and the bulwark theories of which they are a subset match up with federalism as it exists in the world.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.014
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.390
Teacher spread0.372 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it