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Record W2244995491 · doi:10.3998/mpub.8083157

The Deregulatory Moment?

2015· book· en· W2244995491 on OpenAlexaboutno aff
Robert G. Boatright

Bibliographic record

VenueUniversity of Michigan Press eBooks · 2015
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsCampaign financeDeregulationPolitical scienceDemocracyPoliticsContext (archaeology)Supreme courtLawPolitical economyPublic administrationEconomicsGeography

Abstract

fetched live from OpenAlex

For those who assume that increased regulation of political spending is inevitable in democratic nations, recent developments in U.S. campaign finance law appear puzzling. Is deregulation, exemplified by the U.S. Supreme Court's decision in Citizens United v. FEC, a harbinger of things to come elsewhere or further evidence that the United States remains an anomaly? In this volume, experts on the United States, Canada, Great Britain, Australia, Germany, Sweden, France, and several other European nations explore what deregulation means in the context of political campaigns and demonstrate how such comparisons can inform the study of campaign finance in the U.S. Whereas the contributors do not settle on any single theory of change in campaign finance law or any single perspective on the relationship between changes seen in the U.S. and those in other nations over the past decade, they do concur that the U.S. is rapidly retreating from the types of regulations that defined campaign finance law in most democratic nations during the latter decades of the twentieth century. By tracing and analyzing the recent history of regulation, the contributors shed light on many pressing topics, including the relationship between public opinion and campaign finance law, the role of scandals in inspiring reform, and the changing incentives of political parties, interest groups, and the courts.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.815
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.034
GPT teacher head0.189
Teacher spread0.155 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations16
Published2015
Admission routes1
Has abstractyes

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