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Record W3121481061

Saving and Social Security Wealth: A Case of Turkey

2007· preprint· en· W3121481061 on OpenAlexaff
H. Yigit Aydede

Bibliographic record

VenueLoyola eCommons (Loyola University Chicago) · 2007
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSocial securityConsumption (sociology)EconomicsAggregate (composite)TurkishAggregate dataOrder (exchange)EconometricsFinanceMarket economyStatisticsMathematics
DOInot available

Abstract

fetched live from OpenAlex

This paper is the first attempt in the literature to investigate the effects of public social security on aggregate consumption in a time-series setting for a developing country, Turkey that has one of the most generous social security systems in the OECD region. In order to quantify the social security variable, the paper uses the social security wealth (SSW) series calculated for the first time for Turkey and shows that SSW is the largest part of the household wealth in Turkey and therefore should not be ignored in the aggregate consumption studies. After having all sensitivity tests for the major assumptions embedded in the SSW series, it shows that SSW has robust and positive effects on aggregate consumption, and therefore the PAYG system suppresses the Turkish national saving approximately 25% in 2003.

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)0.002
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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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