MétaCan
Menu
Back to cohort
Record W4409428864 · doi:10.1177/23780231251328714

From Funding Equity Initiatives to Research Productivity: Quantifying the Impact of NSF ADVANCE Awards on Recipients’ Publication Trajectories

2025· article· en· W4409428864 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocius Sociological Research for a Dynamic World · 2025
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsEquity (law)ProductivityPolitical scienceEconomicsRegional sciencePublic economicsEconomic growthGeographyLaw

Abstract

fetched live from OpenAlex

Service work in academia, including organizational change efforts, often competes with time for research, potentially affecting academic careers (tenure, promotion, and pay) through slowed publication productivity. However, little is known about how involvement in such efforts affects publication strategies or whether external funding mitigates the potentially negative impacts on research activity. The authors examine changes in publication trajectories among academics participating in the National Science Foundation ADVANCE program, an externally funded gender equity initiative. Using bibliometric data and a matched sample, the authors find that scholars involved in ADVANCE awards published significantly more articles within the first four years after receiving funding. This increase cannot be fully attributed to shifts in research focus, such as publications on gender, or changes in collaboration patterns. Instead, ADVANCE resources created a spillover effect, boosting publications in gender equity while also enhancing productivity in scholars’ primary research areas. These findings suggest that external and institutional resource allocation can offset the additional burdens associated with organizational change work, enabling academics to maintain active research careers while contributing to sustainable change initiatives. This highlights the critical role of robust resource provision in supporting faculty members engaged in organizational change.

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)0.133
metaresearch head score (Gemma)0.404
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1330.404
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0280.149
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0040.003
Research integrity0.0000.002
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 head0.873
GPT teacher head0.738
Teacher spread0.135 · 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