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Record W2897646630 · doi:10.11575/prism/34438

Reflexive legal processes for environmental bridging organizations in the Calgary Region

2016· article· en· W2897646630 on OpenAlexaboutno aff
Judy Stewart

Bibliographic record

VenuePRISM (University of Calgary) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsnot available
Fundersnot available
KeywordsReflexivityBridging (networking)Political scienceSociologyComputer scienceSocial scienceComputer security

Abstract

fetched live from OpenAlex

n Canadian provinces, municipalities are responsible for most land use management on private lands, and are encouraged to protect provincially owned natural resources from local land use impacts. Policy and regulatory gaps exist at the regional-scale for managing municipal land use impacts on natural resources, such as air, water and ecological resources that cross multiple municipal boundaries and jurisdictions. In the Calgary Metropolitan Region in southern Alberta, three multi-stakeholder environmental bridging organizations (the Calgary Regional Partnership, the Bow River Basin Council, and Calgary Regional Airshed Zone) emerged, connecting municipal, public and private stakeholders who shared interests in land use, watershed and airshed management, respectively. These organizations co-created natural resource management plans (co-created plans) to address transboundary and interjurisdictional issues not addressed through provincial laws or municipal bylaws. Because the organizations have no legal mandate or authority, they operate alongside the provincial environmental policy and regulatory system. The Calgary Metropolitan Region provided a demonstration context for conducting transdisciplinary research, combining emerging theories of reflexive law, environmental governance, and bridging organizations. Reflexive legal theory is deliberately applied to support and legitimize the role of environmental bridging organizations in ‘bridging’ environmental policy and regulatory gaps between provincial and municipal authorities at a regional-scale.

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)0.012
metaresearch head score (Gemma)0.024
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.231
Threshold uncertainty score0.619

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.024
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0250.042
Scholarly communication0.0130.005
Open science0.0030.011
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.019
GPT teacher head0.214
Teacher spread0.195 · 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
Published2016
Admission routes1
Has abstractyes

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