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Record W4391444131 · doi:10.1017/s0714980823000788

Not Just One Long Vacation: Revisiting the Importance of Lifestyle Planning in the Transition to Retirement

2024· article· en· W4391444131 on OpenAlexafffund
Christine Ausman

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsPreparednessRetirement planningPsychologyCareer planningRetirement communityFinancial planGerontologySocial psychologyApplied psychologyBusinessActuarial scienceMedicineFinanceManagementPedagogyEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: There is a need to further understand the nature and role of planning for one's lifestyle in retirement. OBJECTIVE: The purpose of this study was to examine retirement planning and how it impacts perceived preparedness and satisfaction with the retirement transition, as well as to explore personal experiences of retirement. METHODS: = 748) fully or partly retired participated in an online survey that included quantitative questions about perceived retirement preparedness and satisfaction and open-ended questions about retirement goals, fears, challenges, and advice. FINDINGS: Results determined that while both financial and lifestyle planning were significant predictors of higher perceived preparedness, only lifestyle planning was a significant predictor for satisfaction. Overall, no gender differences were detected. Open-ended comments highlighted the importance of planning for one's lifestyle in retirement, including meaningful activities and social connections. DISCUSSION: Individualized career advising as well as group-based educational programs or peer-assisted learning initiatives appear warranted to support people in planning for their lifestyle in retirement.

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 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)0.006
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.089
GPT teacher head0.341
Teacher spread0.253 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicRetirement, Disability, and EmploymentFrench-language works237,207