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Record W2907757035 · doi:10.4324/9781351151801-10

Financial Resources in Retirement: The Roles of Pensions and Other Sources

2017· book-chapter· en· W2907757035 on OpenAlexaboutno aff
Peter Scherer

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessFinance

Abstract

fetched live from OpenAlex

This chapter describes the relation between public pension and other income sources in the incomes of retired people, and the interaction between these questions and household composition. It utilizes information collected for the recently published Organisation for Economic Cooperation and Development (OECD) study of financial resources in retirement, which covered nine OECD member countries: the United States, Japan, Germany, the United Kingdom, Italy, Canada, the Netherlands, Finland and Sweden. Social transfers have been an important source of real income growth in most countries, but except in Canada and Japan the impact on income distribution has been either neutral or regressive. The chapter looks at a different, though related, issue: the risk of poverty experienced by vulnerable groups. It explores the crucial role in all countries of public transfers for those with low incomes, but the much greater variety for other income groups.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.003

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 head0.189
GPT teacher head0.382
Teacher spread0.193 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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