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Record W7071537227

STRUCTURE AND DYNAMICS OF FISCAL EQUALIZATION SYSTEMS. A Comparative Analysis of Australia, Canada, Germany, Spain, Switzerland, and the United States

2017· dissertation· fr· W7071537227 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS · 2017
Typedissertation
Languagefr
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Order (exchange)Democratic legitimacy
DOInot available

Abstract

fetched live from OpenAlex

Cette thèse de doctorat analyse les dynamiques des systèmes de péréquation financière. Les systèmes de péréquation financière sont des institutions qui sont crées pour prévenir des conflits qui ont émergé à cause de l'hétérogénéité économique présente dans des pays fédéraux. Ces conflits peuvent avoir un impact sérieux et même mener à la violence ou à la sécession. Cette recherche s'avère donc cruciale pour comprendre ces conflits et pour connaître les effets que les systèmes de péréquation financière peuvent avoir dans la prévention et la résolution des conflits. Cette contribution tente de pallier le manque de recherche systématique sur les systèmes de péréquation financière. Ce thème est largement absent en science politique malgré l'importance des sujets en science politique comme la solidarité, l'union fédérale et la construction d'une nation. De plus, cette dissertation n'analyse pas uniquement les effets statiques, mais aussi les conditions nécessaires au succès de réformes des systèmes de péréquation financière dans la réduction de conflit. Ces dynamiques sont analysées pour six études de cas dans un espace de temps qui commence depuis la fondation de ces six fédérations jusqu'à aujourd'hui. Cela fournit donc une analyse qualitative comparative sur les systèmes de péréquation financière en profondeur qui est sans précédant. Pour cette analyse comparative, un nouveau cadre théorique a été conçu. Cela consiste notamment en une nouvelle typologie des systèmes de péréquation financière mais aussi en une typologie sur des différents types de conflits. Cette recherche compte fournir de base en science politique pour résoudre ou même prévenir des conflits dans l'avenir. -- This doctoral dissertation analyzes dynamics of fiscal equalization systems. Fiscal equalization systems are institutions that are created to prevent conflicts that emerge due to economic heterogeneity in fédéral countries. These conflicts can have a serious impact and lead to violence or secession. This research is thus crucial to understand these conflicts and to learn what effect fiscal equalization systems have in preventing or even fostering such conflicts. This contribution is important as systematic research on fiscal equalization systems is largely absent in political science, even though fundamental political issues are at stake such as solidarity, fédéral union, or nation-building. Moreover, this dissertation looks not only into static effects, but also into the conditions that make reforms of financial equalization systems successful in reducing conflicts. These dynamics are analyzed for six case studies in a time-frame starting from the foundation of these six fédérations until today. It provides thus an unprecedented in-depth qualitative comparative analysis of fiscal equalization systems. For the comparative analysis of these case studies, a new theoretical framework has been established. It notably consists of a new typology of fiscal equalization systems, but also of différent conflict types. This research intends to incite the spark in political science in order to resolve or even prevent these conflicts in the future.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.324
Teacher spread0.298 · 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 designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

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