MétaCan
Menu
Back to cohort
Record W1594187327

FATCA and the Erosion of Canadian Taxpayer Privacy

2014· article· en· W1594187327 on OpenAlexaffabout
Arthur J. Cockfield

Bibliographic record

VenueSSRN Electronic Journal · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsQueen's University
Fundersnot available
KeywordsTaxpayerParliamentLegislationBusinessGovernment (linguistics)BoycottHarmPublic administrationPolitical scienceLawPolitics
DOInot available

Abstract

fetched live from OpenAlex

In 2010, the United States enacted a tax reform known as the Foreign Account Tax Compliance Act (FATCA). Under FATCA, all non-U.S. financial institutions, including Canadian banks, must review their records to determine if any accounts are owned by “U.S. persons,” which include U.S. citizens residing abroad and individuals with significant social and/or economic ties with the United States. The United States threatened to economically sanction any foreign country that did cooperate with the new regime. Accordingly, Canada has agreed to implement FATCA via an intergovernmental agreement (IGA) with the United States; at this writing the implementing legislation, Bill C-31, is before Parliament. This report discusses how FATCA and the IGA unduly harm the privacy interests and rights of Canadians in part because detailed financial information concerning hundreds of thousands of Canadians would be transferred to a foreign government for the first time. Canada is getting nothing in return for this privacy giveaway other than the relief of the threatened economic sanctions. The Canadian government should not implement the IGA until these privacy concerns are addressed.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.007
GPT teacher head0.196
Teacher spread0.188 · 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 designTheoretical or conceptual
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

Citations1
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicTaxation and Legal IssuesFrench-language works237,207