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Record W7037510822

An economic analysis of the potential for market exchanges of ecological goods and services: Two Canadian case studies

2007· dissertation· en· W7037510822 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2007
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGoods and servicesSanctionsProduct marketPublic goodIntermediaryDatabase transactionInterdependenceProduct (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis investigates how to increase the potential for market exchanges of ecological goods and services. This investigation includes the development of a taxonomy of impediments to market exchanges of ecological goods and services and the application of this taxonomy to test which, if any, of these impediments exists for landowners in two Canadian case studies. The case studies reveal that market exchanges of ecological goods and services are already taking place. However, their potential could be increased with institutional developments such as intermediaries to reduce transaction costs. Legal sanctions for trespassing and breached exchange agreements and reduced policy restrictions in the areas of fishing and hunting may also be valuable to extending market exchanges to ecological goods and services. Landowner ability to sell ecological goods and services may be positively correlated with knowledge of the community, joint production, club good provision and product differentiation.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0060.003
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.001
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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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 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
Published2007
Admission routes1
Has abstractyes

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