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Record W7003679328

Introduction

2019· other· en· W7003679328 on OpenAlexaboutno aff

Bibliographic record

VenueUCL Discovery (University College London) · 2019
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSocial network analysisPsychological resilienceMarket structureResilience (materials science)Network theoryHeroinBig dataMarket research
DOInot available

Abstract

fetched live from OpenAlex

Volume I showed that the Big Circle Boys (BCB) dominated the Canadian heroin market in the 1990s as a mono-ethnic criminal network. However, there was evidence that a heroin drought occurred in the early 2000s in Canada and Australia. Volume II sets out to explore how the BCB succeeded and failed on a granular level based on their operations; the connection between the two droughts and the BCB; and the strategic and theoretical implications on their survival as a collective. Martin Bouchard’s drug market resilience framework is the main theory used and related network structure and properties are examined. A research gap in the paucity of studies on ethnic-Chinese drug traffickers in Western countries is identified. Social network analysis is explained as one of the analytical tools used.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.683
Threshold uncertainty score0.974

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.3170.120

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 head0.187
Teacher spread0.184 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

Explore more

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