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Record W2130493148 · doi:10.1061/40792(173)235

Water Management in British Columbia: Issues and Influences

2005· article· en· W2130493148 on OpenAlexaffabout
J. S. Mattison, Melinda Moore

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicArchaeology and Natural History
Canadian institutionsGovernment of British Columbia
Fundersnot available
KeywordsLegislatureWater resourcesClimate changeResource (disambiguation)AssertionEnvironmental resource managementWater supplyEnvironmental planningGeographyPolitical scienceEnvironmental scienceArchaeologyComputer scienceEcology

Abstract

fetched live from OpenAlex

British Columbia is Canada's western most province, bordering Alaska to the northwest, Yukon to the north, Alberta to the east, and Montana, Idaho, and Washington states to the south. British Columbia is richly endowed with water resources, which are an important part of the province's history, culture, and economic development. This paper begins with a brief description of the hydrology of the province, the historical development of the water resources, and the current legislative and management framework. With this background, four key issues or influences that will affect future water resource development in British Columbia will be discussed. One of the first considerations that the Province is addressing is the aboriginal assertion of rights and titles. Treaties with First Nations peoples have only been established in a small part of the Province. Dealing honourably with First Nations' claims will result in the largest allocations of water made this century. Secondly, operational reviews of the 400 major dams in British Columbia are required to ensure that a wide range of social and environmental benefits are achieved in addition to the water supply and power generation, for which the dams were built. Thirdly, we are beginning to realize the effects that climate change is bringing. Processes and resources that enable the people of British Columbia to adapt to climate change through behaviour changes are needed. Finally, as a result of these influences, a revision of our legislative and regulatory framework will be necessary to ensure that we have the right tools to effectively manage our water resources.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.678

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0150.008
Scholarly communication0.0100.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.269
Teacher spread0.261 · 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 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

Citations0
Published2005
Admission routes2
Has abstractyes

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Same topicArchaeology and Natural HistoryFrench-language works237,207