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Record W161853060

Ownership of Rainwater and the Legality of Rainwater Harvesting in British Columbia

2014· article· en· W161853060 on OpenAlexaboutno aff
Katie S. Duke

Bibliographic record

VenueAppeal: Review of Current Law and Law Reform · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsRainwater harvestingPrinciple of legalityWater scarcityLegislationEnvironmental planningWater resource managementWater resourcesEnvironmental scienceBusinessNatural resource economicsLawPolitical scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

In recent years, a growing number of individuals and municipalities have become interested in rainwater harvesting.1 The practice is part of a larger shift towards sustainable building practices and stormwater management.2 However, the legality of rainwater collection in British Columbia is uncertain. At the same time, freshwater resources in the province are increasingly under stress from heavy use and climate change.3 As water scarcity increases, conflicts over rainwater harvesting may result. It is therefore pertinent that the legality of rainwater harvesting be considered so that possible conflicts can be anticipated and areas in need of law reform can be addressed. This paper addresses the issue of whether landowners or occupiers have the legal right to capture rainwater falling onto their property and the nature of that right.4 Upon review of the relevant water-related legislation and applicable common law, it is most likely that rainwater is common property subject to the law of capture. Effectively, rainwater belongs to no one and everyone until it is captured. While landowners do not have a property interest in water until it is captured, their right to harvest rainwater is likely unrestricted and is not subject to concerns of downstream water users.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.700

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0060.008
Scholarly communication0.0070.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.297
Teacher spread0.275 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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