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Record W2915783609 · doi:10.1017/s1355770x18000554

Elephants and mammoths: the effect of an imperfect legal substitute on illegal activity

2019· article· en· W2915783609 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment and Development Economics · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPoachingMammothCITESAfrican elephantPopulationGeographySocioeconomicsArchaeologyEcologyDemographyBiologyEconomics

Abstract

fetched live from OpenAlex

Abstract In response to the CITES ban on trade in elephant ivory, mammoth ivory began to be produced in post-Soviet Russia. We investigate how this substitute to elephant ivory has affected the poaching of elephants. We argue that the early success of the 1989 ivory ban at increasing the African elephant population was driven in part by increasing supply of mammoth ivory. The more recent increases in poaching appear to be driven by increasing demand and falling African institutional quality. We find that absent the 80 tonnes of Russian mammoth ivory exports per annum 2010–2012, elephant ivory prices would have doubled from their $ 100 per kilogram level and that the current poaching level of 34,000 elephants per year may have increased by as many as 55,000 elephants per year on a population of roughly half a million animals.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.694

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.003
GPT teacher head0.172
Teacher spread0.168 · 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