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Record W4389683831 · doi:10.1002/pam.22553

Grads on the go: Measuring college‐specific labor markets for graduates

2023· article· en· W4389683831 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Policy Analysis and Management · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsnot available
FundersInstitute of Education SciencesRussell Sage Foundation
KeywordsQuarter (Canadian coin)InstitutionInvestment (military)Public institutionHigher educationDemographic economicsLabour economicsSocial mobilityEconomicsPolitical scienceBusinessEconomic growthGeographyLaw

Abstract

fetched live from OpenAlex

Abstract This paper introduces a new measure of the labor markets served by colleges and universities across the United States. About 50% of recent college graduates are living and working in the metro area nearest the institution they attended, with this figure climbing to 67% in‐state. The geographic dispersion of alumni is more than twice as great for highly selective 4‐year institutions as for 2‐year institutions. However, more than one quarter of 2‐year institutions disperse alumni more diversely than the average public 4‐year institution. In one application of these data, we find that the average strength of the labor market to which a college sends its graduates predicts college‐specific intergenerational economic mobility. In a second application, we quantify the extent of “brain drain” across areas and illustrate the importance of considering migration patterns of college graduates when estimating the social return on public investment in higher education.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
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 head0.059
GPT teacher head0.246
Teacher spread0.187 · 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