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Record W6991130567

Evaluating Public Participation in Canadian Municipal Climate Change Adaptation Plans

2023· other· en· W6991130567 on OpenAlexaffabout

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsBrock University
Fundersnot available
KeywordsPublic participationVariety (cybernetics)Adaptation (eye)Community participationClimate change adaptationClimate changeProcess (computing)Content analysisPlan (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

This research employs a qualitative content analysis to evaluate public participation in municipal climate adaptation plans in Canada. I conducted quantitative scoring and qualitative coding based on the assessment framework adapted from Uittenbroek et al. (2019). The framework highlights three dimensions of public participation: (a) Who participates, (b) When, and (c) How. This study highlights four key findings. First, the majority of plans do not engage with a wide range of community stakeholders, suggesting that the complete representation of community interests is not being included. Second, participation is occurring throughout the planning process in half of the plans, demonstrating a need to increase the number of opportunities for participation. Third, plans were inconsistent in clearly articulating whether participation influenced decision-making in plan development. Finally, plans are inconsistent in their application of the quantity and variety of participation mechanisms. These findings offer insight into public participation in Canadian municipal adaptation planning.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.753

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0170.007
Scholarly communication0.0060.002
Open science0.0030.007
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.073
GPT teacher head0.266
Teacher spread0.193 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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