Will AmFree Kill the GLOBE?
Bibliographic record
Abstract
The following amicus curiae brief was filed with the Court of Justice of the European Union on November 19, 2025, by Tarcísio Diniz Magalhães, assistant research professor with the University of Antwerp Faculty of Law and Antwerp Tax Academy; Allison Christians, H. Heward Stikeman Chair in Tax Law at McGill University and director of the Canadian Center for Tax Policy; Leyla Ateş, professor of tax law with Kadir Has University Faculty of Law, Türkiye; Reuven S. Avi-Yonah, Irwin I. Cohn Professor of Law at the University of Michigan School of Law; Stjepan Gadžo, associate professor with the University of Rijeka Faculty of Law, Croatia; Young Ran (Christine) Kim, professor of law with the Benjamin N. Cardozo School of Law at Yeshiva University; N. Nilay Dayanç Kuzeyli, assistant professor of tax law with İ.D. Bilkent University Faculty of Law, Türkiye; Jeroen Lammers, assistant professor of international tax law with the Copenhagen Business School; Ivan Ozai, associate professor and Queen’s Faculty Scholar in Tax Law and Policy with Queen’s University, Canada; and Afton Titus, associate professor with the University of Cape Town Faculty of Law, South Africa.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.064 | 0.016 |
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".