MétaCan
Menu
Back to cohort
Record W2033427144 · doi:10.1017/s0144686x1400035x

In line or at odds with active ageing policies? Exploring patterns of retirement preferences in Europe

2014· article· en· W2033427144 on OpenAlexaboutno aff
Dirk Hofäcker

Bibliographic record

VenueAgeing and Society · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveOddsRetirement ageDemographic economicsActive ageingWork (physics)Quarter (Canadian coin)Labour economicsEconomicsOlder peopleGerontologyMedicinePensionGeography

Abstract

fetched live from OpenAlex

ABSTRACT Faced with demographic ageing, European policy makers since the mid-1990s have taken a turn from fostering early retirement to promoting longer working life by reducing early exit incentives and facilitating work continuation. However, it remains open whether these reforms are yet reflected in the retirement plans and preferences of future pensioners’ cohorts. Using most recent data on desired retirement ages from the fifth wave of the European Social Survey (2010/11 wave), this paper empirically investigates how far current policy reforms are in line with the retirement age preferences of older workers aged 45 and over. Results show that older workers approaching retirement ages still intend to retire before the politically envisioned age of 65, and in many cases also before nationally defined standard retirement ages. Despite visible progress in implementing active ageing measures, the challenge of motivating older workers to continue working until or even beyond retirement ages thus remains. At the same time, there are regime-specific problem groups that face difficulties in adjusting to the active ageing paradigm of longer working life. Especially in countries with little employment support, those with unstable work careers, employment interruptions and few financial resources are at a high risk of being crowded out from late career employment and thus from the possibility of ensuring a decent standard of living in old age.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.234
GPT teacher head0.386
Teacher spread0.152 · 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

Citations101
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAgeing and SocietySame topicRetirement, Disability, and EmploymentFrench-language works237,207