Public involvement in health genomics: the reality behind the policies
Bibliographic record
Abstract
Abstract Public involvement is increasingly becoming the norm as stakeholders recognize the need to inform, consult and engage the public. However, there is limited understanding about the meaning and implications of public involvement, in particular elements like the levels of public involvement, the goals of the involvement, the type of public to be involved, the methods of involving the public and the need to assess effectiveness. We conducted a systematic review of policy documents/guidelines published between 1998 and 2009, by governments, health professionals and the public regarding public involvement in the area of human genomics. Documents were identified using the HUMGEN database and organizational web sites. A total of 70 documents were retrieved addressing public involvement and human genomics. The review revealed that 22 documents mentioned the active process of partnership and collaboration, whereas 27 mentioned consultation and 29 mentioned education. The most common goals were building trust and respect, followed by education, governance and lastly, understanding risks and benefits. We found that less than a third of the documents defined who the public is, and when mechanisms for public involvement were mentioned, they were rarely placed into a context. Few documents drew attention to evaluation. It is reassuring to see that there has been an emphasis placed on public involvement in the area of health and genomics. The findings underscore the gaps existing in the actual policy documents/guidelines and the need to clarify the goals, the methods, who is the public, what mechanism are appropriate and the need for evaluation when addressing public involvement in health genomics.
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 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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".