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Record W4411407378 · doi:10.1016/j.jpubeco.2025.105419

Frames, incentives, and education: Effectiveness of interventions to delay public pension claiming

2025· article· en· W4411407378 on OpenAlex
Franca Glenzer, Pierre‐Carl Michaud, Stefan Staubli

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Public Economics · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of CalgaryHEC Montréal
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et CultureSocial Science Research Council
KeywordsIncentiveEconomicsPublic economicsPsychological interventionPensionPublic educationActuarial scienceMicroeconomicsPsychologyFinanceEconomic growth

Abstract

fetched live from OpenAlex

In many retirement income systems, people forgo a higher stream of public pension income by claiming early. This paper provides survey- and quasi-experimental evidence on how increasing financial incentives, educating individuals, and changing the framing of the claiming decision affect pension claiming and the present value of expected pension benefits. We find that all three types of interventions induce delays, but they have heterogeneous financial consequences. Educating participants about the claiming decision and life expectancy leads to claiming ages with higher pension wealth. In contrast, changing the framing of the claiming decision and strengthening financial incentives do not improve, and may even worsen, financial outcomes.

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)0.001
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 score0.154
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.024
GPT teacher head0.274
Teacher spread0.250 · 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