Kindred's International Law: Chiefly as Interpreted and Applied in Canada, 9th ed.
Bibliographic record
Abstract
Kindred’s International Law Chiefly as Interpreted and Applied in Canada, 9th Edition emphasizes the experience and practice of international law from a Canadian perspective both domestically and in foreign relations. A publication of long-standing quality and distinguished reputation, this text has been repeatedly cited as an authority in the Supreme Court of Canada and lower courts for decades. It delivers a comprehensive overview of the foundational concepts, principles, sources, and institutions of the international legal system, and examines specific subject areas of importance in the world today. The ninth edition includes new insights from Gib van Ert, former Executive Legal Officer to the Chief Justice of Canada, and scholars Frédéric Mégret and Payam Akhavan. Additionally, readers will benefit from updated commentary and excerpts on recent treaty developments related to NAFTA and the Trans-Pacific Partnership Agreement. This is the only publication of its kind that can offer its reader the guidance and legal sources required to develop a solid and multifaceted understanding of international law from a Canadian perspective. [From Kindred's International Law: Chiefly as Interpreted and Applied in Canada, 9th Edition | Emond Publishing]
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".