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Record W7019587357

Gender, work and retirement for the baby-boomer cohort in Canada

2016· dissertation· en· W7019587357 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantageMarital statusWork (physics)CohortRetirement agePaid workHealth and Retirement StudyConfidentiality
DOInot available

Abstract

fetched live from OpenAlex

Historically, women have had fewer opportunities than men to contribute to the labour force mainly due to their domestic labour, which place women at a disadvantage during their retirement years compared to men. The aim of this study is to evaluate gender differences while also taking other factors into account in planning for retirement, age at retirement, returning to work after retirement, and the current socio-economic situation of retirees. The 2009 Canadian Community Health Survey – Healthy Aging is the source of data used, and this confidential master file was accessed in a secure location, the Research Data Centre (the Quebec Interuniversity Center for Social Statistics, QICSS). \nResults can be summarized along two main themes. First, they show that gender roles do intersect with the process and the decision-making process of retirement. Level of education and financial situation are intertwined with gender roles such that the socio-economic situation of retirees is largely determined by their marital status and level of education, and retired females are still at a financial disadvantage due to their more limited exposure to the labour force. Moreover, the greater attachment to the labour force for men is apparent as they are more likely to retire later and return to work. Second, the study provides clear evidence that the process of retirement is complex, can vary according to many factors and can also follow a non-linear trend that must be better acknowledged in work about retirement issues. For example, some individuals have no plans to retire either because they cannot afford it or want to continue to work and, in other situations, retirement is not a single life event because some return to work.

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 score0.031
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.128
GPT teacher head0.370
Teacher spread0.242 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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