Sequencing the salmon genome: A deliberative public engagement
Bibliographic record
Abstract
Salmon genomics is an emerging field that represents a convergence between socially important scientific innovation and a politically volatile topic of significant interest to the public. These factors provide a strong rationale for public input. This report describes such input from a public engagement event based on the principles of deliberative democracy. The event involved a random, demographically stratified sample of 25 British Columbians (Canada). While some participants opposed sequencing the salmon genome on principle, on the whole participants responded favourably, citing the value of increased knowledge of human impacts on salmon, potentially slowing or reversing this impact, and assisting sustainable management of salmon resources. Participants discussed many of the potential implications of the sequencing project and formulated recommendations pertaining to regulations, international treaties, public education and engagement. Overall, the project illustrates that the specific design and implementation of this event is capable of producing sound policy advice from the general public on genomic-related issues.
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 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 | 0.078 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.017 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.028 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".