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Record W2011554188 · doi:10.1080/00220480109596103

International Trends in Economics Degrees During the 1990s

2001· article· en· W2011554188 on OpenAlexaboutno aff
John J. Siegfried, David K. Round

Bibliographic record

VenueThe Journal of Economic Education · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicInnovations in Educational Methods
Canadian institutionsnot available
Fundersnot available
KeywordsDegree (music)Business cycleEconomicsDemographic economicsPolitical scienceMacroeconomics

Abstract

fetched live from OpenAlex

Australia, Canada, Germany, and the United States experienced a substantial decline in undergraduate degrees in economics from 1992 through 1996, followed immediately by a modest recovery. This cycle does not conform to overall degree trends, shifts in the gender composition of undergraduate populations, or changing interests of female students in any of the four countries. There is no evidence that changes in the “price” of a degree to students, tightened marking standards or degree requirements, or changes in pedagogical methods caused the cycle. Jobs for economics graduates declined in the United States between 1988 and 1990 and thereafter recovered. With a two-year recognition lag, the pattern of employment prospects fits the U.S. slump in economics degrees perfectly. Unfortunately, employment patterns in the other three countries are inconsistent with the degree cycle. The explanation that fits the economic degree pattern best is interest in business 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.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.046
GPT teacher head0.408
Teacher spread0.361 · 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

Citations39
Published2001
Admission routes1
Has abstractyes

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