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Record W2084619564 · doi:10.1080/14927713.2008.9651398

Time for old friends and grandchildren? Post‐retirement get‐togethers and life satisfaction

2008· article· en· W2084619564 on OpenAlexvenueno aff
Galit Nimrod

Bibliographic record

VenueLeisure/Loisir · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsLife satisfactionOrder (exchange)Sample (material)Demographic economicsPsychologyGerontologySocial psychologyEconomicsMedicineFinance

Abstract

fetched live from OpenAlex

This article examines patterns of participation in get‐togethers and their impact on well‐being in a sample of 383 recently retired individuals in Israel. Results indicated that retirees, regardless of their background, tend to maintain existing patterns of involvement at the same or at increased frequency. However, get‐togethers’ role in successful adjustment to retirement seems to be limited. Only two types of relationships were found to be significant for respondents’ well‐being (with spouses and siblings), while spending time with other family members and friends did not significantly predict their satisfaction with life. These findings led to the conclusion that increasing the participation in get‐togethers may not be a good strategy for facing the challenge posed by the tremendous amount of additional free time following retirement. In order to better adjust to retirement, energies should be reallocated in more satisfying and meaningful directions.

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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.086
GPT teacher head0.351
Teacher spread0.265 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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