Biobanking, public consultation, and the discursive logics of deliberation: Five lessons from British Columbia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Genomics-related "deliberative" public consultations are all the rage. Drawing from theories of deliberative democracy, run by social scientists, governments and non-profit organizations globally, these events can produce valuable insights and governance solutions. There is a danger, however, of "deliberation" being viewed by its new practitioners as a homogenous "tool" due to a marked lack of analysis of the discursive processes at play. This paper addresses this gap, employing the discourse theory of Laclau to analyze small and large group deliberation at a public consultation on biobanking in British Columbia (BC), Canada, during 2007. Ethnographic and transcript analysis reveals small group deliberation to be a two-stage process, operating according to two different discursive logics. The paper concludes with five lessons for theorists and practitioners of deliberative public engagement with science.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
| gpt | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it