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Record W4214541859 · doi:10.1177/01640275221074634

Responding to Disability Onset in the Late Working Years: What do Older Workers do?

2022· article· en· W4214541859 on OpenAlexaboutno aff
Jody Schimmel Hyde, April Yanyuan Wu, Gina Livermore

Bibliographic record

VenueResearch on Aging · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
FundersNational Institute on Disability, Independent Living, and Rehabilitation ResearchU.S. Social Security Administration
KeywordsQuarter (Canadian coin)Health and Retirement StudyPsychologyGerontologyWork (physics)Working ageAge discriminationMedicineLabour economicsEnvironmental healthPopulationEconomics

Abstract

fetched live from OpenAlex

This study uses occupational data from the Health and Retirement Study to document the link between disability onset and occupational transitions among older adults who are working and do not report a disabling condition at age 55. We find that one-quarter of workers go on to experience new disabilities before full-retirement age. Relative to their peers who do not report disabilities, stopping work and significant occupational changes are more common among workers who experience new disabilities. Our results suggest that policies to support labor force attachment might consider the importance of new disability onset and whether employer accommodations might help workers with new disabling conditions remain in the jobs they held when their health began to limit their 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)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
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 head0.384
GPT teacher head0.533
Teacher spread0.149 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

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