International Trade Law: A Comprehensive E-Textbook, Volume 6 Special Sectors (6th edition)
Bibliographic record
Abstract
This book is Volume Six of an Eight-Volume set. All of the Volumes are available in KU ScholarWorks. Links to all eight volumes are available in the Abstracts file in this record. About the Author: Born in Toronto of Indian and Celtic heritage, Rakesh (Raj) Kumar Bhala is a dual Canadian-U.S. citizen prominent in the fields of International Trade Law, Islamic Law (Sharī‘a), and Law and Literature. Raj is a University Distinguished Professor at the University of Kansas, School of Law (KU Law). He is published widely world-wide – authoring over 100 scholarly articles and 13 books, including the International Trade Law Textbook, which has been used at over 100 law schools around the globe. Ingram’s Business Magazine designated him as one of “50 Kansans You Should Know.” Raj has testified before the U.K. Parliament, House of Commons, International Trade Committee, on trade and human rights. Media frequently call upon Raj. Across 65 consecutive months (from January 2017-October 2022), “On Point” was his column on International Law and Economics, which Bloomberg Quint / BQ Prime (Mumbai) published and distributed to approximately 6.2 million readers globally. Raj is a Harvard Law School (HLS) graduate (Cum Laude). As a Marshall Scholar, Raj earned two Master’s degrees, from the London School of Economics (LSE) in Economics, and from Oxford (Trinity College) in Management (Industrial Relations). His undergraduate degree is from Duke (Summa Cum Laude, Phi Beta Kappa), where he was an Angier B. Duke Scholar and double-majored in Economics and Sociology. After HLS, Raj practiced at the Federal Reserve Bank of New York, where he twice won the President’s Award for Excellence thanks to his service as a delegate to the United Nations Conference on International Trade Law (UNCITRAL), along with a Letter of Commendation from the U.S. Department of State. He is a member of the State Department’s Speaker Program. Raj has served in officer positions at the International Bar Association (IBA) and Inter-Pacific Bar Association (IPBA), on the Executive Board of Directors of the Carriage Club of Kansas City (including as Treasurer), and been on the Alumni Association Board of the University School of Milwaukee (USM), his high school alma mater. He is grateful to his USM teachers for a liberal arts education that made all good things possible. Raj loves fitness training, has finished 115 marathons, including the “Big Five” of the “World’s Majors” (Boston twice, New York twice, Chicago twice, Berlin, and London). He enjoys studying Shakespeare and (especially since becoming Catholic at Easter Vigil 2001) Theology – and watching baseball.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.227 | 0.199 |
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".