What sets the conditions for success in community‐partnered evaluation work? Multiple perspectives on a small‐scale research‐practice partnership evaluation
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.275 | 0.472 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.024 | 0.034 |
| Scholarly communication | 0.050 | 0.025 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".