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Record W2966284138 · doi:10.15406/sij.2019.03.00145

Global corporate crime and the sino forest fraud in Canada

2019· article· en· W2966284138 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSociology International Journal · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSecurities Regulation and Market Practices
Canadian institutionsWestern UniversityKing's University College
Fundersnot available
KeywordsBusinessEnvironmental crimeIllegal loggingCriminologyForestryGeographyLoggingSociology

Abstract

fetched live from OpenAlex

Sino-Forest, formed in 1994, was a "stock market darling which promised investors a way to cash in on China's rocketing economic growth by way of a booming domestic forestry business". 1,2The company claimed a market value of over $6 billion dollars and was Canada's largest, publicly-traded forest company.Sino-Forest's billion dollar success came to an abrupt end in June, 2011 when a short-seller investment firm specializing in Asia claimed that the company was a multi-billion dollar Ponzi scheme. 1 Following the allegations, Sino-Forests' stock price and bonds collapsed.As a result, Sino-Forest was forced to file for bankruptcy protection, which was granted.The company was dissolved and taken over by creditors as no buyer could be found.Several of the principles have since been charged with civil securities fraud by the Ontario Securities Commission.This paper examines the intricacies of the Sino-Forest scandal while contributing to a theoretical discussion on the role of structural holes in global capital markets.Here, we invoke Quinney's 3 analysis of capital, Chamblis's 4 notion of structural contradictions, and David Harvey's 5 theory of accumulation by dispossession ( 2004).

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 score0.139
Threshold uncertainty score0.836

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 communication0.0000.001
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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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