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Record W2140033782 · doi:10.1177/1091142105285576

Measures of Fiscal Dependency

2006· article· en· W2140033782 on OpenAlexaffabout
Joe Ruggeri, Yang Zou

Bibliographic record

VenuePublic Finance Review · 2006
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsFiscal sustainabilityDependency ratioEconomicsPopulationFiscal unionFiscal policyDependency (UML)SustainabilityMacroeconomicsFiscal yearFiscal imbalanceFiscal federalismDevelopment economicsFinanceDemography

Abstract

fetched live from OpenAlex

There is a concern in many countries that projected increases in the population age sixty-five and older will impose unsustainable burdens on future generations. These fiscal pressures are often expressed with reference to population dependency ratios. The authors argue that concerns about fiscal sustainability may be legitimate, but the use of population dependency ratios as indicators of fiscal pressures is not. They develop an approach to this issue that includes (1) a comprehensive coverage of the public sector, (2) a new methodology for capturing the fiscal effects of population aging, and (3) the integration of demographic, economic, and fiscal variables. This approach is applied to the Canadian fiscal system for the period from 2002-2003 to 2025- 2026. The results indicate that the current fiscal system is sustainable over the long run and does not incorporate intergenerational inequities.

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)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0100.010
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.126
GPT teacher head0.444
Teacher spread0.319 · 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 designTheoretical or conceptual
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
Published2006
Admission routes2
Has abstractyes

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