MétaCan
Menu
Back to cohort
Record W7110879631 · doi:10.1080/07011784.2025.2543860

Water quality and property values: A meta-analysis and Canadian national benefit assessment

2025· article· en· W7110879631 on OpenAlexaffvenueabout

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsProperty (philosophy)Quality (philosophy)Water qualityWater pollutionWork (physics)Legislation

Abstract

fetched live from OpenAlex

This article synthesizes the water quality hedonic property literature and develops a Canadian freshwater amenity valuation model to derive spatially explicit national benefit estimates. We use over 600 meta-observations from 29 hedonic price studies to estimate price elasticities for changes in water quality measured by Secchi disk depth. We find that a 10% increase in water quality is associated with a 1.60% price increase for residential properties within 500 meters of the lakeshore. A distance-decay effect is observed, with a smaller price premium of 0.08% for properties located 500 to 1,000 meters from the lakeshore. These elasticities are integrated with spatial data to estimate the amenity values of a potential 10% water quality improvement across Canada’s freshwater lakes. The estimated local amenity benefits total $8.2 billion, with Ontario receiving 55% of the benefits and British Columbia experiencing the highest per-household gain among the provinces.

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)0.021
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.557
Threshold uncertainty score0.881

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.018
Bibliometrics0.0050.010
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.002
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 head0.118
GPT teacher head0.253
Teacher spread0.135 · 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 designMeta-analysis
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

Citations2
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Water Resources Journal / Revue canadienne des ressources hydriquesSame topicEconomic and Environmental ValuationFrench-language works237,207