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Record W977284295

Navigating the waters : exploring the roles of provincial water NGOs in decision-making

2014· article· en· W977284295 on OpenAlexvenueno aff
Heather Armstrong

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceStakeholderAdaptation (eye)Collective actionInclusion (mineral)Political scienceBridging (networking)Public relationsPublic administrationEnvironmental resource managementEnvironmental planningKnowledge managementBusinessSociologyGeographyEconomicsSocial science
DOInot available

Abstract

fetched live from OpenAlex

The principles of adaptive water governance blends many of the components of adaptive and comanagement, specifically iterative and social learning to foster adaptation and collective action. While many of the principles of adaptive water governance are still evolving, organizations operating within these contexts can be positioned as boundary or bridging agents concentrating on the science-policy interface or more centrally positioned to facilitate the inclusion and consideration of the multi-stakeholder perspectives at play. This thesis uses a comparative case study combined with a modified grounded theory approach to explore organizational governance arrangements and the roles played by three major water-focused non-governmental organizations (NGOs) in decision-making in British Columbia. An understanding of the challenges and supporting conditions that enhance organizational and actor efficacy within case study NGOs will inform the broader water community of opportunities for collaboration, capacity-building and expanding the roles of NGOs through provincial water governance reform.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.138
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0150.011
Scholarly communication0.0070.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.160
Teacher spread0.155 · 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
Published2014
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)Same topicSustainability and Climate Change GovernanceFrench-language works237,207