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Record W2982291660

The Promises and Pathologies of Presidential Federalism

2018· article· en· W2982291660 on OpenAlexaff
Nicholas Jacobs, Connor M. Ewing

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPresidencyFederalismPresidential systemPolitical sciencePoliticsState (computer science)Context (archaeology)Public administrationCorporate governanceRelevance (law)CentralityLawPolitical economyLaw and economicsSociologyEconomicsGeographyManagement
DOInot available

Abstract

fetched live from OpenAlex

State and local politics have dominated the first year of Donald Trump’s presidency. Despite promises to reinvigorate states’ rights both before and after his campaign, Trump has used the administrative powers of the modern presidency to pursue his policy agenda at the subnational level. From waiving certain provisions of federal programs, to filing lawsuits against states and localities, Trump has taken advantage of the opportunities crafted by his predecessors to use subnational politics for the presidency’s own ends. We place these nascent developments in historical and theoretical context to suggest that “presidential-federalism” at once signifies the continued strength and relevance of subnational governance, while providing occasions for further administrative aggrandizement. Trump, despite remaining highly unconventional in a number of ways, might further reinforce the presidency’s centrality to modern American federalism.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.028
Scholarly communication0.0090.008
Open science0.0000.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.023
GPT teacher head0.337
Teacher spread0.315 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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