MétaCan
Menu
Back to cohort
Record W2109404666 · doi:10.1017/s071498080000204x

Changes in Income within a Cohort over the Later Life Course: Evidence for Income Status Convergence

2002· article· en· W2109404666 on OpenAlexaffabout
Steven G. Prus

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2002
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsCarleton University
Fundersnot available
KeywordsCohortGenerosityLife course approachPosition (finance)Convergence (economics)Socioeconomic statusPensionDemographic economicsDemographyCohort effectPsychologyEconomicsEconomic growthSociologyPolitical scienceMedicineSocial psychologyPopulation

Abstract

fetched live from OpenAlex

ABSTRACT This paper examines the extent to which an individual's income-status position relative to that of others in the same cohort is maintained over the later life course. Changes in the income status of individuals born between 1924 and 1928 are estimated by means of synthetic cohort methods. Using a series of cross-sectional data files from every fifth Survey of Consumer Finances, starting in 1978, the findings show that, from ages 50 to 64, persons of this birth cohort with early-life socio-economic status advantages (namely high education) improve their absolute and relative income status position vis-à-vis others with status disadvantages. For ages 65 to 74, the economic well-being of individuals with status advantages and disadvantages converge. Since Canada's public pension programs are relatively well developed in terms of comprehensiveness and generosity, they do a good job at countering the effects of status background characteristics on the distribution of income in old age. In the absence of these programs (i.e., up to age 64), the relative position of those with high education and other advantaged groups is strengthened.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.351
Teacher spread0.299 · 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.

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

Citations3
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicGlobal Health Care IssuesFrench-language works237,207