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Record W2883370322 · doi:10.24357/igjr.4.1.712

Intergenerational Justice in Public Finance: A Canadian case study

2019· article· en· W2883370322 on OpenAlexaffabout
Paul Kershaw

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPopulation ageingPer capitaPublic financeEconomic JusticeReciprocity (cultural anthropology)Demographic economicsEconomicsPopulationPublic expenditurePublic economicsEconomic growthSociologyDemographySocial science

Abstract

fetched live from OpenAlex

This study examines whether Canadian governments have adapted budgets for the ageing population in accordance with norms of intergenerational justice. Public finance data in 2016 are analysed compared to 1976 in light of three constructs: the elderly/non-elderly ratio of social spending change, intergenerational reciprocity, and ability to pay. Findings include that (i) governments increased per capita spending for seniors 4.2 times faster than for those under the age of 45; (ii) public finance requires younger Canadians to contribute 22%-62% more in income taxes for the elderly now by comparison with 1976; and (iii) the contemporary ageing population has a greater ability to pay than cohorts immediately before and after them.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.137
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.011
Science and technology studies0.0220.004
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.469
GPT teacher head0.672
Teacher spread0.203 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

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