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Record W4415286476 · doi:10.3386/w34366

Who Rides Out the Storm? The Immediate Post-College Transition and its Role in Socioeconomic Earnings Gaps

2025· report· W4415286476 on OpenAlexfundno aff
Judith Scott-Clayton, Verónica Minaya, CJ Libassi

Bibliographic record

VenueNational Bureau of Economic Research · 2025
Typereport
Language
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
FundersMcGill UniversitySid W. Richardson FoundationSmith Richardson Foundation
KeywordsEarningsSocioeconomic statusTransition (genetics)PopulationPanel data

Abstract

fetched live from OpenAlex

Despite a large earnings premium for bachelor's degree completion in general, graduates from lowincome families earn substantially less than graduates from high-income families.While prior research has documented the role of college quality and major choice in explaining these gaps, we examine undermatching on a different margin: the first (post-college) job transition.The transition from college to the labor market can be challenging to navigate, and students with financial, informational, or other disadvantages during the job search may be more likely to "undermatch" to their first job.Using administrative data from a large, urban, public college system, we document large gaps in earnings five years after graduation by SES (proxied by financial aid receipt) that remain unexplained even after controlling for GPA, college, field of study, and other pregraduation characteristics.We then examine how features of the initial job transition relate to longer-term earnings, and to what extent differences in the first job transition can explain later SES earnings gaps.Our results show that first job transitions are rocky for many graduates, strongly predict earnings at Year 5, and are a substantial mediator of socioeconomic gaps in earnings five years after college graduation-reducing the unexplained gap by almost two-thirds.

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)0.030
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.125
GPT teacher head0.494
Teacher spread0.368 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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