Public engagement pathways for emerging GM insect technologies
Bibliographic record
Abstract
Policy and management related to the release of organisms generated by emerging biotechnologies for pest management should be informed through public engagement. Regulatory decisions can be conceptually distinguished into the development of frameworks, the assessment of the release of a specific modified organism, and implementation decisions such as location and timing. Although these decisions are often intertwined in practice, the negotiation takes place at different stages of technology development and suggests different roles for public engagement. Some approaches to public engagement are more appropriate for different purposes and situations, and it is not always obvious how to go about matching the approach to the purpose. In addition to the diverse technologies involved in generating modified organisms, there are diverse publics with particular interests and different kinds of knowledge. Institutional interests range from commercial development to public regulation and future uptake. Contextual features, such as agency mandates, may limit or structure the extent and approach to public engagement. Different convening groups (government agencies, public interest groups, academics, businesses) and the kind of decision that is being considered determine what kind of input is needed and how the engaging groups will be constituted. This paper considers how the context of the release of genetically modified insects for pest control requires expanding approaches to the design of the public engagement.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".