A protocol for co-creating research project lay summaries with stakeholders: guideline development for Canada’s AGE-WELL network
Bibliographic record
Abstract
BACKGROUND: Funding bodies increasingly require researchers to write lay summaries to communicate projects' real-world relevance to the public in an accessible way. However, research proposals and findings are generally not easily readable or understandable by non-specialist readers. Many researchers find writing lay summaries difficult because they typically write for fellow subject specialists or academics rather than the general public or a non-specialist audience. The primary objective of our project is to develop guidelines for researchers in Canada's AGE-WELL Network of Centres of Excellence, and ultimately various other disciplines, sectors, and institutions, to co-create lay summaries of research projects with stakeholders. To begin, we produced a protocol for co-creating a lay summary based on workshops we organized and facilitated for an AGE-WELL researcher. This paper presents the lay summary co-creation protocol that AGE-WELL researchers will be invited to use. METHODS: Eligible participants in this project will be 24 AgeTech project researchers who are funded by the AGE-WELL network in its Core Research Program 2020. If they agree to participate in this project, we will invite them to use our protocol to co-produce a lay summary of their respective projects with stakeholders. The protocol comprises six steps: Investigate principles of writing a good lay summary, identify the target readership, identify stakeholders to collaborate with, recruit the identified stakeholders to work on a lay summary, prepare for workshop sessions, and execute the sessions. To help participants through the process, we will provide them with a guide to developing an accessible, readable research lay summary, help them make decisions, and host, and facilitate if needed, their lay summary co-creation workshops. DISCUSSION: Public-facing research outputs, including lay summaries, are increasingly important knowledge translation strategies to promote the impact of research on real-world issues. To produce lay summaries that include information that will interest a non-specialist readership and that are written in accessible language, stakeholder engagement is key. Furthermore, both researchers and stakeholders benefit by participating in the co-creation process. We hope the protocol helps researchers collaborate with stakeholders effectively to co-produce lay summaries that meet the needs of both the public and project funders.
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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 | 0.265 | 0.355 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.045 | 0.018 |
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".