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Record W4206709871 · doi:10.1017/s1049096521001487

Political Science at the NSF: The Politics of Knowledge Production

2022· article· en· W4206709871 on OpenAlexafffund
Tamir Moustafa

Bibliographic record

VenuePS Political Science & Politics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Science Research and Education
Canadian institutionsSimon Fraser University
FundersSimon Fraser UniversityNational Science Foundation
KeywordsFraming (construction)PoliticsPreparednessPolitical sciencePublic relationsResearch programPublic administrationEngineering ethicsEngineeringLaw

Abstract

fetched live from OpenAlex

ABSTRACT The National Science Foundation (NSF) recently replaced its long-standing Political Science Program with two new programs: the Security and Preparedness Program and the Accountable Institutions and Behavior Program. This article evaluates the likely impact of the reform by way of original survey data. The NSF Program Change Survey asked past recipients of the Political Science Program Standard Grant to evaluate their own previously funded proposals according to the new NSF program descriptions. Respondents were asked whether they would apply for the same research project under the new thematic programs and, if they would, whether they believed it would be necessary to change the framing or substance of their proposal. Data from the survey suggest that the new NSF program themes are likely to discourage some political scientists from applying, while encouraging many more applicants to shift the framing or substance of their research to accommodate the new call for proposals. In particular, the new Security and Preparedness Program carries significant consequences for new knowledge production.

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)0.037
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0100.022
Scholarly communication0.0200.011
Open science0.0010.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0120.001

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 head0.063
GPT teacher head0.428
Teacher spread0.364 · 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 designQualitative
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

Citations2
Published2022
Admission routes2
Has abstractyes

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