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Record W2969542179 · doi:10.1177/0160017619869788

The Hope Fulfilled? Measuring Research Performance of Universities in the Economic Crisis

2019· article· en· W2969542179 on OpenAlexaff
Qiantao Zhang, Paige A. Clayton, Shiri M. Breznitz

Bibliographic record

VenueInternational Regional Science Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinancial crisisAtlantaEconomicsPolitical scienceEconomic growthBusinessAccountingPublic economicsMacroeconomicsMetropolitan areaGeography

Abstract

fetched live from OpenAlex

The economic and financial crisis of 2008–2013 caused most universities to revisit their traditional funding allocations. In a time of budget constraints, some universities have been able to enjoy an increasing level of research expenditure, while other aspects of their budgets have been cut. This article analyzes changes in research funding and output at three research universities in Atlanta, Georgia, between 2002 and 2015, covering periods both before and after the crisis. Although the amount of research expenditure has continued to increase in the three universities after the crisis, the efficiency of research funding has declined. The results argue that the approach undertaken by governments and universities after the crisis has been partial and too narrowly focused on the financial terms of research to take into consideration many relevant factors constraining research performance of academics.

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)0.018
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0010.003
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.001
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 head0.087
GPT teacher head0.410
Teacher spread0.323 · 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.

Study designObservational
DomainEvaluation
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

Citations4
Published2019
Admission routes1
Has abstractyes

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