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Record W3023199880 · doi:10.1002/jcop.22372

What sets the conditions for success in community‐partnered evaluation work? Multiple perspectives on a small‐scale research‐practice partnership evaluation

2020· article· en· W3023199880 on OpenAlex
Parissa J. Ballard, Lynn Rhoades, Lori Fuller

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

VenueJournal of Community Psychology · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsImpact
FundersWake Forest Clinical and Translational Science Institute, Wake Forest School of MedicineNational Institutes of HealthNational Center for Advancing Translational SciencesKate B. Reynolds Charitable Trust
KeywordsGeneral partnershipScale (ratio)Foundation (evidence)Work (physics)Public relationsBest practiceKnowledge managementPsychologyMedical educationEngineering ethicsPolitical scienceMedicineComputer scienceEngineering

Abstract

fetched live from OpenAlex

The goals of this study are: (a) to share reflections from multiple stakeholders involved in a foundation-funded community-partnered evaluation project, (b) to share information that might be useful to researchers, practitioners, and funders considering the merits of researcher/practitioner evaluation projects, and (c) to make specific suggestions for funders and researcher/practitioner teams starting an evaluation project. Three stakeholders in a small-scale research-practice partnership (RPP) reflected on the evaluation project by responding to three prompts. A researcher, community organization leader, and funder at a small foundation share specific tips for those considering a small-scale RPP. Engaging in a small-scale RPPs can be a very meaningful experience for individual researchers and smaller organizations and funders. The benefits and challenges align and differ in many ways with those encountered in larger projects.

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)0.135
metaresearch head score (Gemma)0.048
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1350.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.801
GPT teacher head0.681
Teacher spread0.120 · 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