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Record W3201086369 · doi:10.1111/roiw.12538

Vietnam Era Fathers: The Intergenerational Transmission of Tertiary Education

2021· article· en· W3201086369 on OpenAlexaff
Louis N. Christofides, Michael Hoy, Joniada Milla, Thanasis Stengos

Bibliographic record

VenueReview of Income and Wealth · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNature versus nurtureAttendanceContext (archaeology)Educational attainmentCohortLotteryDemographic economicsPopulationHigher educationEconomicsEconomic growthPsychologyDemographySociologyMedicineGeography

Abstract

fetched live from OpenAlex

A strong positive correlation between the educational attainment of parents and their children is well documented. Determining whether this relationship is due to nature (selection) or nurture (causal factors) is both a challenge and an important policy issue. We use the Vietnam era draft lottery and educational exemptions as a “natural experiment” to address this issue. Substantially more men attended university during this war, creating a cohort of fathers many members of which would not normally have enrolled in tertiary education (TE). Using US Current Population Survey (CPS) and Study of Income Dynamics (PSID) data on the father’s and his children’s TE involvement, we find that, for this war cohort, the intergenerational transmission leading their children to enrollment in TE is at least as high (CPS) or even higher (PSID) than that of control cohorts. In the context of university attendance in the US, these findings suggest that nurture plays an important additional role.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.367
Teacher spread0.339 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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