Comparing methods of ethical consultation for biotechnology related issues.
Bibliographic record
Abstract
This paper provides a brief summary of the final public consultation event conducted as part of the Democracy, Ethics, and Genomics: Consultation, Deliberation and Modelling [DEG] project at the W. Maurice Young Centre for Applied Ethics [CAE] at the University of British Columbia [UBC]. (1) The all day event took place in Vancouver, British Columbia on Saturday, September 24, 2005. The DEG project, funded by both Genome Canada and Genome BC, compares two methods of ethical analysis for the development of public policy in the area of (2) Primary Investiator Dr. Mike Burgess leads a team conducting focus groups with various publics in order to identify the moral dimensions and perspectives of issues raised by participants. (3) Dr. Peter Danielson leads the Norms Evolving in Response to Dilemmas [NERD] team, which uses web-based surveys in their research. These surveys typically include twelve questions that support deliberative decision-making by providing participants with access to five advisors who offer scientific, policy, ethical, and pro and con advocate advice. (4) The dual objectives of this one-day event were: (1) to compare and contrast DEG project methods using salmon genomics as the common topic; and (2) have participants develop and rate a list of public consultation criteria. Individuals were randomly recruited from Vancouver and were paid a $100 honorarium for their participation. The final sample included people somewhat familiar with computers, who did not have prior or expert knowledge of genomics or salmon aquaculture. The sample also included individuals of all ages and filtered for an even gender split. The day began by separating participants (n = 41) into two similarly sized cohorts. Members of cohort A participated in one of three two-hour focus groups while those in cohort B completed a NERD survey (of approximately one hour) followed by an hour-long open discussion of the survey. The cohorts then came together for a two-hour group deliberation that began with a ten-minute overview from a participant from one of the three focus groups and from the NERD group. The overview presented some of the groups' conclusions regarding salmon genomics. Participants also had an opportunity to discuss their experiences thus far in the process and to speak to points on which the groups converged and diverged, and reasons for their conclusions. All participants were then encouraged to take part in developing criteria that identifies information or processes the participants believe are necessary to make good decisions in consultation processes, such as the one they had just completed (regarding salmon genomics). This discussion was led by a list of pre-determined consultation criteria compiled by DEG team members. These initial criteria addressed aspects of effective public consultation that could be used to evaluate the DEG project methods. A senior facilitator used these criteria to guide the group consultation process, only presenting the criteria if they were overlooked during the group discussion. The group conclusions and pre-determined criteria were then inserted randomly into a web-based survey. Participants used this survey to evaluate the conclusions and consultation standards during the last stage of the event. The exit survey took participants (n=37) approximately thirty minutes to complete and was divided into four sections (1) public representation, (2) engaging and reasonable process, (3) informed opinions, and (4) process outcome. The results discussed in the remainder of this paper fall under the fourth section of the survey. Preliminary findings indicate this consultation event was a success. Nearly three-quarters (74%) somewhat or strongly agreed that the conclusions reached by this type of consultation process should direct regulatory policy. Results also indicate that almost all (94%) participants would be willing to engage in this type of event again. …
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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 | 0.305 | 0.527 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 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; 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".