Bibliographic record
Abstract
Why this book? This book begins with an overview of residence of individuals in private international law, with a particular emphasis on general principles on residence and conflict of law rules. It then examines issues raised by residence of individuals in EC (non-tax) law. Individual country surveys provide in-depth analyses from a national viewpoint. The following countries are discussed: Australia, Austria, Belgium, Canada, France, Germany, Italy, Japan, Netherlands, Spain, Switzerland and United Kingdom. This book is essential reading for all those dealing with issues of taxation of individuals in an international context. Downloads Sample excerpt, including table of contents This book is part of the EC and International Tax Law Series View other titles in the series Editor(s) Guglielmo Maisto Contributors Asatsuma Akiyuki, John Avery Jones, Philip Baker, Aagje Bellens, Kim Brooks, Veronika Daurer, Luc De Broe, Michael Dirkis, Stefano Dorigo, Augusto Fantozzi, James J. Fawcett, Anna Gunn, Jean Pierre Le Gall, Marika Lemos, Nicolas Message, Angelo Nikolakakis, Mercedes Nuñez Grañon, Thierry Obrist, Roland A. Pfister, Alexander Rust, Jacques Sasseville, Jonathan Schwarz, María Teresa Soler Roch, Ed Stuart and Jan Wouters.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.025 | 0.012 |
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".