Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.037 | 0.013 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".