Synthesising the outputs of deliberation: Extracting meaningful results from a public forum
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
Recent years have seen an increase in empirical studies of public deliberation. This has led to important advances in thinking through issues such as who to include, how best to inform lay audiences about a particular topic, and how to maximise the perceived legitimacy of deliberation. An important issue that has not received much attention is how to define, identify, and report the results of deliberation. The conversations among individuals that occur over the course of a deliberation can be understood as a large and complex set of qualitative data. The deliberative discourse that is produced over the course of a public deliberation contains a large number of statements by participating individuals, and it is not immediately obvious how certain statements might be extracted to characterise the official results of the deliberation. In particular, public deliberation aims to guide deliberants towards collective decisions – therefore, social scientific methods of analysis that do not orient to changes in individual deliberants’ positions at best only capture a part of what is going on. Further, qualitative analyses such as thematic or content analyses may give equal importance to considered and informed positions produced nearer to the end of a deliberative event and relatively uninformed and preliminary positions expressed at the beginning. While such analyses can provide important insights, they are therefore not sufficient on their own for identifying the results of deliberation. In this paper, I argue that the results of a deliberative forum are best conceptualised as constituted by at least three distinct factors: 1) the initial framing and structuring of the deliberation; 2) the facilitation process; and 3) the final (post-hoc) collation and analysis of materials by an analyst or host of the deliberation. I conclude that any meaningful and legitimate representation or synthesis of the results of deliberation should take into account the complexity of the discourse that is produced in such settings. The recent case of the BC BioLibrary Deliberation is used to illustrate and ground the discussion.
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.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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