Stakeholder and Citizen Roles in Public Deliberation
Bibliographic record
Abstract
This paper explores theoretical and practical distinctions between individual citizens (‘citizens’) and organized groups (‘stakeholder representatives’ or ‘stakeholders’ for short) in public participation processes convened by government as part of policy development. Distinctions between ‘citizen’ and ‘stakeholder’ involvement are commonplace in government discourse and practice; public involvement practitioners also sometimes rely on this distinction in designing processes and recruiting for them. Recognizing the complexity of the distinction, we examine both normative and practical reasons why practitioners may lean toward—or away from—recruiting citizens, stakeholders, or both to take part in deliberations, and how citizen and stakeholder roles can be separated or combined within a process. The article draws on a 2012 Canadian-Australian workshop of deliberation researchers and practitioners to identify key challenges and understandings associated with the categories of stakeholder and citizen and their application, and hopes to continue this conversation with the researcher-practitioner community.
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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 | 0.074 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.063 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".