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Record W4414031391 · doi:10.23987/sts.149512

Transforming Excellence?

2025· article· en· W4414031391 on OpenAlex
Lisette Jong, Thomas Franssen, Stephen Pinfield

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.

fundA Canadian funder is recorded on the work.
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

VenueScience & Technology Studies · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchAustrian Science FundFondazione TelethonWellcome TrustSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMichael Smith Health Research BCNational Science Foundation
KeywordsExcellencePolitical scienceLaw

Abstract

fetched live from OpenAlex

‘Excellence’ is omnipresent in the research ecosystem but the focus on excellence is increasingly controversial. This paper contributes to the excellence debate through an empirical study of how notions of excellence are used in eight research funding organizations. Because research funding organizations are shaped by the excellence regime, and constrained by both governmental policy and scientific elites, funders cannot simply resort to a debunking critique and do away with excellence altogether. To navigate the ambiguous relationship to excellence, the approach to excellence is shifting from it being taken as a ‘matter of fact’ to a ‘matter of concern’ that needs to be unpacked and reconfigured. In mitigation strategies funders attempt to reconfigure excellence by patching, pluralizing and transforming their activities around excellence. We argue that a transformation of the research ecosystem is unlikely to happen when underlying assumptions about competition and meritocratic ideals are not also problematized.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.621
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0010.002
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 head0.026
GPT teacher head0.283
Teacher spread0.256 · 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