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Record W2993103502 · doi:10.1017/s1474747219000416

Retirement incentives and behavior of private and public sector workers

2020· article· en· W2993103502 on OpenAlex
Courtney Coile, Susan Stewart

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

VenueJournal of Pensions Economics and Finance · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsIncentivePrivate sectorPublic sectorPensionQuarter (Canadian coin)Labour economicsWork (physics)Demographic economicsFinancial sectorBusinessEconomicsEconomic growthFinance

Abstract

fetched live from OpenAlex

Abstract Over the past several decades, private sector workers in the USA with employed-sponsored pensions have experienced a dramatic shift from defined benefit (DB) to defined contribution plans, while this trend has been less pronounced for public sector workers. In this paper, we use data from the Health and Retirement Study to explore changes in the retirement incentives and retirement behavior of public and private sector workers over the past quarter-century. We find that both groups have become less likely to report having a DB pension or any pension. Compared to their private sector counterparts, public sector workers have a higher level of retirement wealth and a larger financial gain from continued work at older ages, and these differences by sector are growing across cohorts. Both groups respond to financial incentives in making retirement decisions. However, growing differences by sector in the gain to continued work do not appear to have translated into diverging retirement behavior, as we observe similar trends in the two 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.044
Threshold uncertainty score0.231

Codex and Gemma teacher scores by category

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

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 head0.183
GPT teacher head0.350
Teacher spread0.168 · 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