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Record W2770079438 · doi:10.1177/0898264317742810

Socioeconomic Position Across the Life Course and Cognitive Ability Later in Life: The Importance of Considering Early Cognitive Ability

2017· article· en· W2770079438 on OpenAlexaff
Else Foverskov, Erik Lykke Mortensen, Anders Holm, Jolene Masters Pedersen, Merete Osler, Rikke Lund

Bibliographic record

VenueJournal of Aging and Health · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsWestern University
FundersNordForsk
KeywordsLife course approachCognitionSocioeconomic statusPsychologyDanishEducational attainmentCohortGerontologyDevelopmental psychologyAssociation (psychology)DemographyMedicinePsychiatryPopulation

Abstract

fetched live from OpenAlex

Objective: Investigate direct and indirect associations between markers of socioeconomic position (SEP) across the life course and midlife cognitive ability while addressing methodological limitations in prior work. Method: Longitudinal data from the Danish Metropolit cohort of men born in 1953 ( N = 2,479) who completed ability tests at age 12, 18, and 56-58 linked to register-based information on paternal occupational class, educational attainment, and occupational level. Associations were assessed using structural equation models, and different models were estimated to examine the importance of accounting for childhood ability and measurement error. Results: Associations between adult SEP measures and midlife ability decreased significantly when adjusting for childhood ability and measurement error. The association between childhood and midlife ability was by far the strongest. Discussion: The impact of adult SEP on later life ability may be exaggerated when not accounting for the stability of individual differences in cognitive ability and measurement error in test scores.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.417
Teacher spread0.366 · 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

Citations34
Published2017
Admission routes1
Has abstractyes

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