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Record W6912627384 · doi:10.5281/zenodo.6957403

From Intent to Impact-The Decline of Broader Impacts throughout an NSF Project Life-Cycle

2022· article· en· W6912627384 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Science and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsAttritionDiversity (politics)PopulationInterpretation (philosophy)EnforcementQuarter (Canadian coin)Population decline

Abstract

fetched live from OpenAlex

Our findings indicate a systematic decline in impacts from the proposal stage, abstracts, to the conclusion of the project, project outcome report. Impacts decline in all but four categories (13 of 17) and all but two directorates (5 out of 7). Across the sample, impacts decline by 14%, but the decline is most pronounced when the impacts are intrinsic to the research or targeted at marginalized groups. This finding is troublesome given the NSF’s commitment to broaden participation by engaging underrepresented groups. Grants with inclusive impacts have less funding and prove more difficult to achieve. By contrast, grants report more impact for advantaged groups from the abstract to the POR. From this finding, it appears the interpretation and enforcement of BI policy is not currently serving marginalized groups. This lack not only maintains the status quo, but may hinder the development of scientific thought due to an absence of diversity society. Impacts that serve the general population suffer less attrition than inclusive impacts, but these still make up less than a quarter of impacts achieved by the end of the research period.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0220.001

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 head0.067
GPT teacher head0.383
Teacher spread0.316 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicInternational Science and DiplomacyFrench-language works237,207