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Record W4385422404 · doi:10.1007/s10344-023-01708-9

Illegal trade of pangolins in India with international trade links: an analysis of seizures from 1991 to 2022

2023· article· en· W4385422404 on OpenAlexaff
Lalita Gomez, Tito Joseph, Sarah Heinrich, Belinda Wright, Neil D’Cruze

Bibliographic record

VenueEuropean Journal of Wildlife Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsWildlife Conservation Society Canada
FundersU.S. Fish and Wildlife ServiceWorld Animal Protection
KeywordsPangolinPoachingWildlife tradeWildlifeGeographyEndangered speciesSocioeconomicsBusinessEcologyBiologyEconomicsHabitat

Abstract

fetched live from OpenAlex

Abstract Pangolins have become one of the most intensely poached and trafficked mammal species, exploited mainly for the food and traditional medicine trade. Intense and continued illegal exploitation for commercial trade has become the leading cause of pangolin declines in parts of Asia and Africa. Recent research has illustrated the growing threat this poses to pangolins in India. India is home to two species of pangolin, the Indian Pangolin Manis crassicaudata and the Chinese Pangolin M. pentadactyla , which have been assessed as endangered and critically endangered respectively. Pangolin seizures in India between 1991 and 2022 were analysed to gain a better understanding of illegal trade dynamics. A total of 426 seizures were collated, involving an estimated 8603 pangolins. The frequency of pangolin seizures increased over time as did the volume of estimated pangolins seized. This could be due to a range of different factors including rising poaching and trade levels, increased law enforcement and reporting, and awareness. Nevertheless, on the ground, investigations by the Wildlife Protection Society of India strongly indicate that the escalating poaching and trade in pangolins is driven by lucrative market demands from beyond India’s borders, with a growing focus on the trade in live pangolins. Enforcement efforts appear to be undermined by low prosecution rates with only 1.4% of recorded seizures resulting in successful convictions. Asian pangolins have rapidly disappeared from their natural range and been locally extirpated in many parts of East and Southeast Asia. India’s pangolin species are at similar risk if poaching and trafficking levels continue unmitigated.

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)0.004
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 score0.020
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.315
Teacher spread0.277 · 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.

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

Citations10
Published2023
Admission routes1
Has abstractyes

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