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Record W7035015925

Zvláštní úloha Quebeku v kanadské fiskální federaci

2019· dissertation· en· W7035015925 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2019
Typedissertation
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsFiscal federalismIncentiveSubsidyFederalismPaymentGovernment (linguistics)Fiscal capacityConvergence (economics)Equalization (audio)Transfer payment
DOInot available

Abstract

fetched live from OpenAlex

Canadian fiscal federalism is a set of complex relations on both federal and interprovincial levels. As each province faces different geographic, economic or demographic situation, federal government runs equalization program that aims to diminish potential economic gaps. Despite vaguely defined purpose, the transfers are unconditional - provinces could use them for any purpose they find appropriate. That could possibly cause distorted incentives such as flypaper effect in which politicians tend to adjust spending behavior according to source of income. Equalization payments are distributed based on potential capacity of each province to raise revenue. As Quebec has been the largest recipient of equalization grants with slow, if existent, convergence to the rest of provinces, it is subject of the analysis in the period from the year 1981, which marks breaking points in both Quebec and equalization system history, to 2016. Quebec tends to be blamed for taking advantage of the system by deliberately undervaluing its fiscal capacity through subsidized prices of electricity and by boosting its social expenditures. By incorporating descriptive statistics and discussion, this thesis concludes that Quebec's policymakers likely deliberately implement fiscal policies that in turn undervalue its fiscal...

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.349
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.249
Teacher spread0.242 · 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.

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
Published2019
Admission routes1
Has abstractyes

Explore more

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