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Does Population Aging Affect Income Inequality?

2021· book-chapter· en· W3169327512 on OpenAlex
Gürçem ÖZAYTÜRK, Ali Eren Alper, Fındık Özlem Alper

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAdvances in human services and public health (AHSPH) book series · 2021
Typebook-chapter
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsDependency ratioCointegrationEconomicsDemographic economicsInequalityEconomic inequalityPensionDependency (UML)PopulationLabour economicsDemographyEconometricsSociologyMathematics

Abstract

fetched live from OpenAlex

This study analyzes the relationship between the elderly dependency ratio and income inequality over the period 1972-2019 in countries such as the USA, Japan, the UK, France, Germany, Canada, and Italy, which rank top in the population aging, using the Fourier-Shin cointegration test. According to the results, the rise in the elderly dependency ratio of all countries included in the analysis, except for France, has a positive impact on income inequality. The result implying that the rise in the elderly dependency ratio increases the income inequality and renders some policy recommendations possible. Accordingly, the provision of adequate childcare programs and family aids can result in greater labor force participation in the short- and long-run. In addition, a pension system can be developed to lower the elderly dependency ratio, more money can be saved for the retirement period, and working domains can be developed for the post-retirement period.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.005
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.421
Teacher spread0.376 · 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