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Record W6904628979 · doi:10.14288/1.0340930

Navigating the Tensions in Collaborative Watershed Governance : Water Governance and Indigenous Communities in British Columbia, Canada

2018· article· en· W6904628979 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Collections · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceIndigenousScholarshipCollaborative governanceLegislatureNatural resourceWater resourcesNatural resource management

Abstract

fetched live from OpenAlex

First Nations in British Columbia (BC), Canada, have historically been—and largely continue to be—excluded from colonial governments’ decision-making and management frameworks for fresh water. However, in light of recent legal and legislative changes, and also changes in water governance and policy, there is growing emphasis in scholarship and among legal, policy and advocacy communities on shifting water governance away from a centralized single authority towards an approach that is watershed-based, collaborative, and involves First Nations as central to decisionmaking processes. Drawing on community-based research, interviews with First Nations natural resource staff and community members, and document review, the paper analyzes the tensions in collaborative water governance, by identifying First Nations’ concerns within the current water governance system and exploring how a move towards collaborative watershed governance may serve to either address, or further entrench, these concerns. This paper concludes with recommendations for collaborative water governance frameworks which are specifically focused on British Columbia, but which have relevance to broader debates over Indigenous water governance.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0320.001
Scholarly communication0.0020.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.270
Teacher spread0.259 · 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 teacher head, not a consensus.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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