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A Parallel Approach to Water Stewardship Planning

2021· article· en· W3136240276 on OpenAlexafffundvenueabout
Robert Patrick, Warrick Baijius

Bibliographic record

VenueCanadian Planning and Policy / Aménagement et politique au Canada · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsIndigenousStewardship (theology)Land-use planningState (computer science)Integrated business planningEnvironmental planningEstate planningPolitical scienceIndigenous cultureTraditional knowledgeSociologyGeographyLand useManagementEngineeringComputer scienceCivil engineeringLawEcologyPoliticsEconomics

Abstract

fetched live from OpenAlex

The professional practice of planning and the state-controlled mechanisms under which western-science planning operate offer little to improve the lives of Indigenous people and their communities. Arguably, western-science planning along with its many legal tools, collectively reproduce existing colonial relations in the interest of state domination over, and suppression of, Indigenous people. In this paper, we describe a different planning model, one that Viswanathan (2019) refers to as “parallel planning”, wherein Indigenous planning principles are practiced in parallel to western-science planning, with each approach informing, and complementing, the other. Our case example is from the Saskatchewan River Delta wherein Indigenous values nested in traditional knowledge in the land and water are the centrepiece of a planning process supported by the western-science planning framework. Challenges facing this approach will be discussed alongside suggestions on how these challenges may be overcome.

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)0.011
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 score0.148
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0080.024
Scholarly communication0.0120.008
Open science0.0030.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.001

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 head0.022
GPT teacher head0.288
Teacher spread0.266 · 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

Citations4
Published2021
Admission routes4
Has abstractyes

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