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Record W2474170485 · doi:10.2166/wp.2005.0030

Watershed management: review of Canadian diversity

2005· article· en· W2474170485 on OpenAlexaffabout
Catherine Senecal, Chandra A. Madramootoo

Bibliographic record

VenueWater Policy · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsMcGill University
Fundersnot available
KeywordsWatershed managementWatershedStakeholderCorporate governanceGovernment (linguistics)Context (archaeology)Environmental resource managementBusinessWater resourcesDiversity (politics)Unit (ring theory)Environmental planningPublic administrationPolitical scienceGeographyPublic relationsEcologyEconomicsComputer science

Abstract

fetched live from OpenAlex

Watershed management combines the concept of the watershed as the most appropriate spatial management unit for water resources and the concept of integrated water resources management. The movement toward this form of management has resulted in the emergence of new forms of governance in Canada. The Canadian water management context has resulted in various forms of river basin management organizations co-existing within the same country. Four examples are presented of river basin management organizations as they have evolved in Ontario, British Columbia, Quebec and the Prairies, with emphasis on government policy, organizational structure, roles and responsibilities, sources of funding and implementation of integrated watershed management programs and policies. These case studies are selected because they range from government institutions to organizations partially supported by government, to grass roots and stakeholder involvement models, reflecting different levels of funding and stakeholder participation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.208
Teacher spread0.185 · 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 designNot applicable
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

Citations3
Published2005
Admission routes2
Has abstractyes

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