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Record W6926615548 · doi:10.25384/sage.c.6290115

International Cash Conduits and Real Estate Empires: A Case Study in Canadian Philanthropic Crime

2022· other· en· W6926615548 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2022
Typeother
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCashReal estateHarmLiabilityClosing (real estate)Scope (computer science)Estate

Abstract

fetched live from OpenAlex

We analyze an instance of philanthropic law-breaking by a group of Canadian charities, who funnelled millions in tax-exempt funds to foreign recipients. Analyzing 20 years of tax data, we identify a pattern of regulatory violation we are calling the burner charity phenomenon. We track a chronological sequence of organizational behaviour characterized by hibernation, growth, and abandonment, across three linked burner charities. Backstopping burner charities, we show, is a network of public and private foundations. We argue that the purpose of burner charities is to enable foundations to transfer funds to foreign agents while remaining shielded from Canadian law. Combining insights from white collar crime and a Zemiology, we conclude by considering the multi-faceted dimensions of harm associated with burner charities.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0140.004
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.074
GPT teacher head0.386
Teacher spread0.312 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations0
Published2022
Admission routes1
Has abstractyes

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