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Record W2936861807 · doi:10.3390/w11040809

Whose Rules? A Water Justice Critique of the OECD’s 12 Principles on Water Governance

2019· article· en· W2936861807 on OpenAlexaff
Katherine Selena Taylor, Sheri Longboat, R. Quentin Grafton

Bibliographic record

VenueWater · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversity of Guelph
FundersAustralian Government
KeywordsIndigenousCorporate governanceHuman rightsPolitical scienceReinterpretationEconomic JusticePublic administrationSociologyEnvironmental ethicsPolitical economyLawEconomicsEcologyManagement

Abstract

fetched live from OpenAlex

The article constructively critiques the Organization for Economic Cooperation and Development’s (OECD) 12 Principles on Water Governance (the OECD Principles). The human rights standard, the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), provided the foundation for conceptualizing Indigenous water rights. The analysis used a modification of Zwarteveen and Boelens’ 2014 framework of the four echelons of water contestation. The analysis indicates that the OECD Principles assume state authority over water governance, make invisible Indigenous peoples’ own water governance systems and perpetuate the discourses of water colonialism. Drawing on Indigenous peoples’ water declarations, the Anishinaabe ‘Seven Grandfathers’ as water governance principles and Haudenosaunee examples, we demonstrate that the OECD Principles privilege certain understandings of water over others, reinforcing the dominant discourses of water as a resource and water governance based on extractive relationships with water. Reconciling the OECD Principles with UNDRIP’s human rights standard promotes Indigenous water justice. One option is to develop a reinterpretation of the OECD Principles. A second, potentially more substantive option is to review and reform the OECD Principles. A reform might consider adding a new dimension, ‘water justice,’ to the OECD Principles. Before reinterpretation or reform can occur, broader input is needed, and inclusion of Indigenous peoples into that process.

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)0.014
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.044
Scholarly communication0.0120.008
Open science0.0020.007
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0020.000

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 head0.253
Teacher spread0.240 · 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 designTheoretical or conceptual
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

Citations44
Published2019
Admission routes1
Has abstractyes

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