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Record W1485824912

Canadian Experience with Watershed Protection and Governance

2012· article· en· W1485824912 on OpenAlexaboutno aff
Jamie Benidickson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceWatershedEnvironmental planningBusinessEnvironmental resource managementPolitical scienceGeographyEnvironmental scienceComputer scienceFinance
DOInot available

Abstract

fetched live from OpenAlex

This paper will survey the status of watersheds in the Canadian legislative and regulatory framework at the federal and provincial levels. While some watershed-oriented regimes such as Conservation Authorities in the province of Ontario have been in place for a number of decades there have been numerous recent developments. These have been encouraged in part by source water protection planning as encouraged through the work of the Walkerton Inquiry and to some degree in conjunction with the Watershed Initiative of the International Joint Commission. Notable provincial initiatives are evident in Quebec, Ontario, Alberta, and Nova Scotia or are under consideration in British Columbia. In addition to general frameworks that operate on a province-wide basis, several highly localized or watershed-specific arrangements have been put in place. Several of these (Lake Simcoe, Ontario, and the Okanagan Basin, B.C., for example) will be examined in detail. Apart from formal legislative arrangements, watershed governance initiatives have emerged through the work of citizen organizations and environmental ngos (Fraser River Council; Ottawa Riverkeeper; Lake of the Woods Water Sustainability Foundation, for example) The proliferation of watershed initiatives in all forms is noteworthy, as is the multi-stakeholder/ governance-oriented configuration of many of the existing arrangements. The paper will provide some preliminary assessment of notable strengths and weaknesses observed to date, accompanied by reflections on the influence of various objectives (public health; economic development and security; maintenance of ecological services and so on) that have contributed to the current round of watershed-based planning and decision-making.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.998

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)0.0030.000

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 head0.009
GPT teacher head0.173
Teacher spread0.164 · 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 designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

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