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Record W3010942292 · doi:10.1111/opn.12313

Identifying contemporary early retirement factors and strategies to encourage and enable longer working lives: A scoping review

2020· review· en· W3010942292 on OpenAlex
Donna M. Wilson, Begoña Errasti‐Ibarrondo, Gail Low, Pauline O’Reilly, Fiona Murphy, Anne Fahy, Jill Murphy

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.

Bibliographic record

VenueInternational Journal of Older People Nursing · 2020
Typereview
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChecklistPensionWork (physics)PsychologySocial securityPopulation ageingPublic relationsGerontologyPopulationNursingMedicineBusinessPolitical scienceEnvironmental healthFinance

Abstract

fetched live from OpenAlex

AIM: Accelerating population ageing is raising concern in many countries now in relation to the availability of workers for essential work roles and responsibilities. A scoping research literature review was done to identify factors currently associated with early retirement and contemporary strategies to encourage and support longer working lives. METHODS: Using the PRISMA-ScR Checklist, we searched the Directory of Open Access Journals and EBSCO Discovery Service for published 2013-2018 research articles using the keyword/MeSH term "early retirement"; 54 English-language articles in peer-review journals were reviewed. RESULTS: Seven early retirement factors were revealed: Ill health, good health, workplace issues, the work itself, ageism, social norms and having achieved personal financial or pension requirement criteria. Six suggested solutions, none proven effective, were identified: Occupational health programmes, workplace enhancements, work adjustments, addressing ageism, changing social norms and pension changes. CONCLUSIONS: The evidence base on early retirement prevention is not strong, with qualitative investigations needed for in-depth understandings of early retirement influences and mixed-methods studies needed to test early retirement prevention solutions for their effects. IMPLICATIONS FOR PRACTICE: Until more evidence is available, every organisation should perform an early retirement risk assessment and identify current versus needed policies and programmes to encourage and enable more middle-aged and older people to work longer.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.878
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.366
GPT teacher head0.505
Teacher spread0.139 · 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