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Record W4389629297 · doi:10.2305/eknn8645

The value of natural capital in Canada’s national parks and national marine conservation areas

2023· article· en· W4389629297 on OpenAlex
Dan Mulrooney, Brenda Jones

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePARKS · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsParks Canada
FundersUniversity of Ottawa
KeywordsNatural capitalVisitor patternNatural resourceNatural resource economicsValue (mathematics)Capital (architecture)BusinessTotal economic valueNational accountsEconomic impact analysisEcosystem servicesGeographyEnvironmental resource managementEnvironmental protectionEconomicsEcosystemEcology

Abstract

fetched live from OpenAlex

Growing attention is being given to protected areas and the ability of their natural capital assets to provide a varied and long-term stream of benefits to individuals and society in general. These areas are often heralded for ensuring natural capital assets persist, but value is often limited to the economic impact of visitor expenditures and the associated effects on regional and national economies. Few studies have attempted to quantify the economic value of natural capital assets in protected areas, especially in Canada. This study uses a benefit transfer approach to produce an initial estimate of the potential economic value of ecosystem services and natural capital associated with the terrestrial and marine environments in Canada’s federal system of national parks and national marine conservation areas. The results suggest that the economic value of these assets ranges between CA$ 156 billion and CA$ 588 billion annually.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.037
GPT teacher head0.201
Teacher spread0.163 · 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