Into the fog? Stakeholder input in participatory impact assessment
Bibliographic record
Abstract
A new development in the more formal and the informal procedures for assessment and project appraisal in the West is the renewed attention paid to citizen participation. The bottleneck in many of these participatory processes is the convergence and selection of the variety of stakeholder inputs (that is, values, interests, suggestions, criteria and opinions) that often lead to results not (wholly) recognisable to participants. The production of a spatial plan in the municipality of De Bilt, the Netherlands, is discussed, to illustrate and analyse the elements that determine the survival of stakeholder input in impact assessment and project appraisal in participatory public policy-making.
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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 | 0.096 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.045 |
| Scholarly communication | 0.019 | 0.040 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 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".