MétaCan
Menu
Back to cohort
Record W2130781355 · doi:10.1002/hec.1050

Schooling, cognitive ability and health

2005· article· en· W2130781355 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Economics · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsSaskatchewan Health Quality CouncilUniversity of Calgary
Fundersnot available
KeywordsNexus (standard)CognitionDemographic economicsQuarter (Canadian coin)Population healthInstrumental variablePopulationEducational attainmentPsychologySubsidyEconomicsGerontologyDemographyMedicineEconomic growthEnvironmental healthEconometricsGeographySociology

Abstract

fetched live from OpenAlex

A large literature documents a strong correlation between health and educational outcomes. In this paper we investigate the role of cognitive ability in the health-education nexus. Using NLSY data, we show that one standard deviation increase in cognitive ability is associated with roughly the same increase in health as two years of schooling and that cognitive ability accounts for roughly one quarter of the association between schooling and health. Both schooling and ability are strongly associated with health at low levels but less related or unrelated at high levels. Estimates treating schooling as endogenous to health suggest that much of the correlation between schooling and health is attributable to unobserved heterogeneity; the causal effect of schooling on health is large only for respondents with low levels of schooling and low cognitive ability. An implication is that policies which increase schooling will only increase health to the extent that they increase the education of poorly-educated individuals. Subsidies to college education, for example, are unlikely to increase population health.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.154
GPT teacher head0.448
Teacher spread0.294 · 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