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Multi-Level Democracy

2020· book· en· W4231424162 on OpenAlexaffabout
Lori Thorlakson

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDemocracyPolitical scienceComputer scienceLawPolitics

Abstract

fetched live from OpenAlex

Abstract All federal systems face an internal tension between divisive and integrative political forces, striking a balance between providing local autonomy and representation on one hand and maintaining an integrated political community on the other hand. How multi-level systems strike this balance depends on the development of styles of either integrated politics, which creates a shared framework for political competition across the units of a federation, or independent politics, preserving highly autonomous arenas of political life. This book argues that the long-term development of integrated or independent styles of politics in multi-level systems can be shaped by two key elements of federal institutional design: the degree of fiscal decentralization, or how much is ‘at stake’ at each level of government, and the degree to which the allocation of policy jurisdiction creates legislative or administrative interdependence or autonomy. These elements of federal institutional design shape integrated and independent politics at the level of party organizations, party systems, and voter behaviour. This book tests these arguments using a mixed-method approach, drawing on original survey data from 250 subnational party leaders and aggregate electoral data from over 2,200 subnational elections in seven multi-level systems: Canada, the United States, Australia, Austria, Germany, Switzerland, and Spain. It supplements this with configurational analysis and qualitative case studies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.578
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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.

Opus teacher head0.193
GPT teacher head0.393
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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

Citations36
Published2020
Admission routes2
Has abstractyes

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