Community Engagement in Genetic Research: Results of the First Public Consultation for the Quebec CARTaGENE Project
Bibliographic record
Abstract
OBJECTIVE: This paper presents the results of the first public consultation for the creation of a large-scale genetic database, the Quebec CARTaGENE project. A consultation has been undertaken in order to gauge whether the general public is receptive to the project. An integral part of the approach of the researchers is to establish a dialogue with the public. METHODS: Two independent expert groups have carried out qualitative and quantitative studies measuring knowledge of and interest in genetics, incentives and obstacles to CARTaGENE participation and comprehension and evaluation of the communication tools. RESULTS: CARTaGENE is seen to hold promise for the greater population. However, reported across qualitative and quantitative studies is the concern for confidentiality and respect for the individual, transparency, the donor's right to feedback and governance. Participation would be conditional on a response to those concerns and a greater dissemination of information. CONCLUSION: Community engagement in genetic research requires targeted communications, with an appropriate proportioning of information and communication, and a consideration of the 'values and personal interests' of individuals according to different societal segments.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".