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Record W4393869991 · doi:10.1017/cts.2024.270

296 Investing in Community-Led Research Capacity Building: New Seed Grant Type

2024· article· en· W4393869991 on OpenAlex
Jen Brown, Claudia Galeno-Sanchez, Corella Payne, Sista Yaa Simpson, P.A.N. Reddy, Pedro Serrano

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

VenueJournal of Clinical and Translational Science · 2024
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
FundersCanadian Centre for Applied Research in Cancer ControlNorthwestern University
KeywordsLibrary scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES/GOALS: We will describe the community-driven development and impact of the new Community Research Capacity-Building grants from the Alliance for Research in Chicagoland Communities, Northwestern University. Communities expressed that to enter equitably into partnerships with academics they need support to build their own community research capacity. METHODS/STUDY POPULATION: ARCC Seed Grants, since 2008, included Partnership Development and Research Pilots, which are both jointly submitted by a community-academic partnership. The new Community Grants are submitted only by community partners and don’t require an academic partner. These grants, $3,000 over 6 months, support the development or strengthening of organizational or community-level research capacity. This may include assessing community capacity to lead and/or collaborate on research; building research capacity of community organizations (staff, leadership, residents), developing community infrastructure (e.g. research principles; staff research responsibilities; process for assessing/ tracking researcher inquiries; template memorandum of understanding) or community research priorities, etc. RESULTS/ANTICIPATED RESULTS: Eight ARCC Community Research Capacity-Building Seed Grants have been awarded so far as a part of three cycles of applications over 2022-23 (2 in 2022, 6 in 2023). During this time period, data has been collected during the application process, in final reports, and in informal group and individual discussions. Information about the profile of grantees (community representation, health focus, etc.), the initial impact of grants, and feedback from grantees about the positive and challenging aspects of the grants will be shared. Grantees have informally shared that the awards have helped to address concerns that many low-income communities of color have their voices are not adequately included in research and other decision-making. The poster will be co-presented by a community grant recipient. DISCUSSION/SIGNIFICANCE: To ensure that research partnerships are community-driven & equitable, it is necessary to invest in community research capacity-building. More evaluation is needed to understand the grants impact, as well as other approaches to community research capacity and leadership development. Poster will be co-presented by a community grant recipient.

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)0.038
metaresearch head score (Gemma)0.071
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.071
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.700
GPT teacher head0.623
Teacher spread0.077 · 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