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Record W7017733514

Bird TakeâDeath Trade

2017· article· en· W7017733514 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLegal and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRulemakingTreatyWildlifeExternalityResource (disambiguation)Service (business)SuperfundNatural resource
DOInot available

Abstract

fetched live from OpenAlex

The Migratory Bird Treaty Act (MBTA) protects 1,027 bird species—the vast majority of native birds in the United States and its territories—by criminalizing the taking, killing, or selling of any migratory bird or bird part.3 Beginning in the 1960s, the Fish and Wildlife Service (FWS) began prosecuting industrial firms for “incidental take,” the unintentional taking or killing of migratory birds. Incidental take is a negative externality of industry: firms kill birds—a natural resource shared by all—and do not compensate for their loss. A split in authority consequently arose on whether the strict liability misdemeanor of the MBTA criminalizes such unintentional killings. In response to concerns of incidental take, the FWS is now in a rulemaking process, by which it hopes to establish an incidental-take permit program, allowing firms to purchase take permits, compensate the FWS for estimated bird take, and evade or at least minimize the risk of prosecution. \n While the incidental-take circuit split has already received scholarly attention elsewhere, this Article tackles a larger conservation question, drawing on scholarship in the fields of emissions trading and conservation banking. This Article proposes two alternative market-based solutions to the menace of incidental take. First, the Bird Tax: a Pigouvian tax that seeks to correct the inefficient market outcome that results in uncompensated industrial and nonindustrial incidental take. Second, the North American Bird Market: a trilateral initiative building upon decades of successful environmental cooperation between Canada, the United States, and Mexico. By incentivizing clean energy, requiring industry to internalize its bird take, and promoting habitat restoration, the Bird Market is an efficient and clean theoretical solution to the menace of incidental take and the looming threat to our continent’s shared birdscape. \n In contrast to a comprehensive, upstream Bird Tax that targets both industrial and nonindustrial incidental take, the Bird Market would entail potentially restrictive financial and logistical costs due to its limited focus on the regulation of industrial take. As such, it is possible that the Bird Market is a mere flight of fancy—a thought experiment whose doom radiates from its very core—and nothing more. Despite these challenges, this Article’s presentation of the Market serves three other purposes. First, the Market serves as a vehicle to expose the sobering truth that the MBTA and incidental-take prosecutions are an expressive, but ultimately fruitless conservation mechanism. Second, the Market is an investigation of how to quantify and trade death with the goal of conserving life. Finally, the exposition of the Market and the critique of the MBTA is an attempt to tightrope walk the seemingly unbridgeable legal-analytical rift between the ritualized law and economics of Ronald Coase,4 and the touchy-feelythrow-your-hands-up-in-the-air neorealism of Arthur Allan Leff. Ultimately, because incidental industrial take is only a minor anthropogenic stressor, the Market will fail to achieve meaningful conservation goals for the same reasons that incidental-take prosecutions under the MBTA fail to achieve these goals. August 2016 marked the centennial of the first migratory bird treaty with Canada. One hundred years have passed, and this Article calls upon Congress to abandon its ancient conservation precepts and supplement our treaties and the MBTA with a meaningful international habitat-restoration program.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.019

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 head0.035
GPT teacher head0.206
Teacher spread0.171 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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