Case Global: News from the International Law Centers & Institutes
Bibliographic record
Abstract
Vol. 6 [sic] [5], #1 (2013) Special Report: Professors help establish accountability mechanisms for Syrian atrocities A Message from Dean Scharf Worth Reading--Recent Faculty Publications/Activities Case launches New Online LLM Case Professor’s New Book Explores Accelerated Formation of Customary International Law Case law grad appointed UN/Africa Union Chief Mediator for Darfur Case launches new exchange and concurrent degree programs with 21 foreign partners Case offers world’s first free online international law course International Law Talk Radio from Case celebrates its first year Case International Law Moot Court teams excel again in 2013 Record number of foreign lawyers received LLM degrees from CWRU in 2013... The American Lawyer features PILPG – a prestigious NGO with special ties to CWRU Alumni spotlights (Andres Perez and Danielle Fritz) News from our Canada-US Law Institute In the past 5 years, 155 Case Law students have interned at 98 placements in 37 countries Recent Graduate Profiles (Christopher Rassi and Nathan Quick and others) 2012-2013 Major Events Round Up Save the Date -- Upcoming Events
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.197 | 0.068 |
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".