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Record W1539297527

Exploring the Governance Landscape of Indigenous Peoples and Water in Canada – An Introduction to the Special Issue

2013· article· en· W1539297527 on OpenAlexaffabout
Julia Baird, Ryan Plummer

Bibliographic record

VenueIndigenous policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsBrock University
Fundersnot available
KeywordsCorporate governanceIndigenousPoliticsPolitical scienceWater resourcesQuality (philosophy)Water qualityScale (ratio)Environmental resource managementEnvironmental planningEnvironmental ethicsBusinessGeographyLawEcologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Access to water of sufficient quality and adequate quantity is a global concern. In excess of one billion people world-wide experience poor water quality or inadequate amounts of water, and many of these people are indigenous (Boelens, Chiba and Nakashima, 2006). The World Water Assessment Programme (2003:4) accordingly argued that “this crisis is one of water governance, essentially caused by the ways in which we mismanage water”. Diagnosing the crisis as a matter of governance highlights the complicated and dynamic social landscape of societal decision-making. Many actors are involved, roles and responsibilities are contested, and multi-scale influences need to be carefully considered. It requires attention to institutions (formal and non-formal), policies and practices. Water governance is broadly understood as “the range of political, social, economic and administrative systems that are in place to develop and management water resources, and the delivery of water services, at different levels of society” (Rogers and Hall, 2003:2).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.227
Teacher spread0.215 · 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.

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

Citations6
Published2013
Admission routes2
Has abstractyes

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