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Choosing to Retire? A Study of Women’s Patterns for Retiring or Continuing to Work

2021· article· en· W3170844409 on OpenAlexaffvenueabout
Isabelle Marchand, Diane‐Gabrielle Tremblay

Bibliographic record

VenueInterventions économiques · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversité TÉLUQUniversité du Québec en Outaouais
Fundersnot available
KeywordsSpouseBaby boomObligationWork (physics)Retirement ageNarrativePaid workDemographic economicsLabour economicsGerontologyPsychologySociologyEconomicsPolitical scienceDemographyMedicinePensionLaw

Abstract

fetched live from OpenAlex

Women of the baby-boom generation are the first generation of women to present an old age-retirement trajectory similar to the traditional male model. Using a narrative approach, we collected 20 life stories from older women, mostly retired, all born in Canada. We present five patterns that influenced respondents’ decisions to end their career or, inversely, postpone the moment of retirement: 1) “Choosing myself” to fully take advantage of the retirement years; 2) Rational retirement: the deliberate choice to stop paid employment and mourn one’s career; 3) The break: obligation to retire; 4) Retirement as an extension of the retirement of a spouse-breadwinner, and 5) Postponing retirement. Our analysis reveals that patterns vary, depending on socio-economic contexts and state of health, relationship to work, spouse’s retirement status, care work, and the desire for freedom. They also reflect life-long social roles associated with care work, remunerated work, housework, and civic commitments. The Aging-retirement trajectory depends on women’s collective and individual histories and the impact of gender on other intersecting social relations.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.339
GPT teacher head0.478
Teacher spread0.140 · 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

Citations4
Published2021
Admission routes3
Has abstractyes

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