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Record W7009656392

Fiscal Federalism in Canada

2000· other· en· W7009656392 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2000
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFiscal federalismFederalismGovernment (linguistics)PoliticsState (computer science)Qualitative analysisFocus (optics)
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this report is to explain the major dynamics affecting fiscal federalism in Canada. It is written primarily for an audience that does not have an extensive knowledge of Canada but it does make use of terms and concepts that are common in the study of fiscal federalism. The major figures in Canadian fiscal federalism are the federal and provincial governments. Territorial governments, local governments and the newly emerging models of aboriginal self-government are significant figures in fiscal relations in Canada, and they receive some attention in the report, but the main focus of this analysis is on the relationship between the federal government and the provinces. The content of the report combines material from the study of economics and political science to provide both a quantitative and qualitative analysis of fiscal federalism in Canada. The report focuses on explaining the current relationship between governments but in doing so a significant amount of attention is given to explaining the historical developments that have led to the current situation.

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)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.205
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0180.004
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.005
GPT teacher head0.161
Teacher spread0.156 · 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
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

Citations0
Published2000
Admission routes1
Has abstractyes

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