Involving Citizens and Patients in Health Research
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.
Bibliographic record
Abstract
The Canadian Institutes of Health Research's (CIHR), Canada's premier health research funding agency, is moving forward in realizing a more systematic, ongoing integration of citizens' input in priority setting, governance and funding programs and tools. In 2008, the Canadian Institutes of Health Research (CIHR) developed a Framework for Citizen Engagement. This Framework establishes guidelines for implementing a more systematic approach to consulting and engaging citizens, such as in assessing the merit and relevance of research applications, developing strategic plans, setting research priorities and for strengthening their role on CIHR's governance committees. This paper describes the current context for public consultation in Canada's federal health care system, the new CIHR citizen engagement framework and discusses citizen engagement activities and efforts undertaken by CIHR institutes and branches. It reviews the methods used by CIHR to engage citizens in four key focus areas: 1. Representation on CIHR's Boards and Committees; 2. Corporate and Institute strategic plans, priorities, policies, and guidelines; 3. Research priority setting and integrated knowledge translation; 4. Knowledge dissemination and public outreach. In discussing CIHR's experiences, the paper identifies some of the challenges and benefits of engaging citizens in CIHR's research processes, including participating in decision making and informing strategic priorities.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it