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Record W2910428990 · doi:10.5070/v427110519

Science and Scholarship Abused, and the Counter-Productive “Conservation” of Wolves in North America and Europe

2016· article· en· W2910428990 on OpenAlexaff
Valerius Geist

Bibliographic record

VenueProceedings - Vertebrate Pest Conference · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsScholarshipWildlifeDenialConservation scienceWildlife conservationExtinction (optical mineralogy)Environmental ethicsConservation biologyLegislationGeographyEthnologyBiodiversityEcologyPolitical scienceSociologyBiologyLawPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Although science forms the basis of wildlife conservation in the North American Model of Wildlife Conservation, advocacy and inadequate scholarship have led to conservation legislation that is destroying the wolf as a species. “Wolf science” is flawed due to the denial of historical information about wolves, ignoring how wolves explore new prey, ignoring long-standing research on the social organization and its changes in wolves, ignoring hybridization as a cause of the genomic extinction, the use of genetic data without a taxonomic verification of specimen, misuse of mathematics, and espousing meaningless statistics. Wolves cannot be conserved as a species in settled landscapes. So called wolf conservation in North America and in Europe is in need of reevaluation, as it is destroying a genuine canid species.

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)0.022
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0110.032
Scholarly communication0.0190.014
Open science0.0010.012
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0060.001

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 head0.013
GPT teacher head0.206
Teacher spread0.192 · 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.

Study designQualitative
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

Citations1
Published2016
Admission routes1
Has abstractyes

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