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Record W2023348403 · doi:10.3152/147154601781767212

Into the fog? Stakeholder input in participatory impact assessment

2001· article· en· W2023348403 on OpenAlex
René Monnikhof, Jurian Edelenbos

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImpact Assessment and Project Appraisal · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsStakeholderCitizen journalismVariety (cybernetics)BottleneckPublic participationEnvironmental planningProject appraisalParticipatory rural appraisalStakeholder engagementParticipatory planningEnvironmental resource managementImpact assessmentParticipatory GISStakeholder analysisPlan (archaeology)BusinessPolitical sciencePublic administrationPublic relationsComputer scienceOperations managementGeographyEngineeringEconomics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.066
GPT teacher head0.433
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it