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Record W7017811412

Catalan Grievances: Do Fiscal Flows Matter?

2017· article· en· W7017811412 on OpenAlexaboutno aff

Bibliographic record

VenueDipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsnot available
FundersMinisterio de Economía y Competitividad
KeywordsCatalanFiscal federalismSample (material)Current accountBalance (ability)Fiscal adjustmentFiscal policy
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this article is to examine the fiscal flows produced by the actions of the Spanish central public sector concerned with Catalonia and their main determinants. We also compare the Catalan fiscal balance with that of rich territories in other countries (Australia, Belgium, Canada, the USA, Spain and Italy). To this aim the article examines, first, whether the methodology used in Catalonia meets international standards; second, whether the Catalan fiscal deficit is indeed among the largest in a sample of territories analysed; third, which are its main determinants. The methodology for calculating fiscal balances is found to be fairly standardised internationally, revealing that Catalonia has a structural fiscal deficit of between 6 and 8 percent of GDP, according to whether the benefit or the flow approach is applied. These figures are a consequence, to a large extent, of the Spanish system of financing the Autonomous Communities. Finally, we briefly discuss whether the fiscal flows can justify, at least partially, the current secessionist process of Catalonia.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.007
GPT teacher head0.259
Teacher spread0.251 · 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 designObservational
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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