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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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.644
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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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