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Duck Hunting and Wetland Conservation: Compromise or Synergy?

2003· article· en· W2026816789 on OpenAlexvenueno aff
Jeff Bennett, Stuart M. Whitten

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsWetlandCompromiseGeographyIncentiveWildlifeWelfare economicsProfit (economics)Cost–benefit analysisEthnologyEnvironmental ethicsPolitical scienceEcologyEconomicsSociologyLawPhilosophy

Abstract

fetched live from OpenAlex

Duck hunting is an issue — often controversial — that generates both benefits and costs to society. Hunters enjoy benefits from engaging in their sport, while those who have ethical concerns regarding the shooting of ducks endure costs. Some in the community fear that duck hunting puts pressure on the continued ecological viability of the hunted species, while others argue that the demand for hunting provides sufficient economic incentive for wetland conservation. Whether society as a whole should permit or restrict duck hunting is to some extent an empirical question: Are the costs to society of allowing duck hunting greater or less than the benefits it generates? Evidence presented in this paper addresses this question. The benefits enjoyed by people who hunt ducks in the upper south east of South Australia are estimated using the travel cost method. The ethical costs borne by the general community because of duck hunting are estimated using the choice modeling technique. Finally a threshold value analysis is used to assess the activities of Wetlands and Wildlife, a not‐for‐profit organization that manages wetlands in part for hunting.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.071
GPT teacher head0.163
Teacher spread0.091 · 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 teacher head, not a consensus.

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

Citations19
Published2003
Admission routes1
Has abstractyes

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