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Record W1964216141 · doi:10.2202/1558-9544.1180

The Effects of Adolescent Health on Educational Outcomes: Causal Evidence Using Genetic Lotteries between Siblings

2009· article· en· W1964216141 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.

Bibliographic record

VenueForum for Health Economics & Policy · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsSocioeconomic statusInstrumental variableOverweightHuman capitalInheritance (genetic algorithm)PsychologyDevelopmental psychologyEmpirical evidenceAdolescent healthMental healthDemographyObesityMedicineEnvironmental healthBiologyEconomicsEconometricsPsychiatryGeneticsPopulationSociology

Abstract

fetched live from OpenAlex

There has been growing interest in using specific genetic markers as instrumental variables in attempts to assess causal relationships between health status and socioeconomic outcomes, including human capital accumulation. In this paper, we use a combination of family fixed effects and genetic marker instruments to estimate the causal effects of poor adolescent mental and physical health status on years of completed schooling. By exploiting the genetic variation in inheritance within families, this empirical strategy presents a unique opportunity to isolate the variation in genetic factors from other dynastic and family characteristics. We present evidence that inattentive symptoms in early childhood have large lasting effects in reducing completed schooling. We also find little consistent evidence that adolescent overweight status influences years of schooling completed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.739
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.113
GPT teacher head0.469
Teacher spread0.356 · 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