LEGAL FLOWS: CONTRIBUTIONS OF EXILED LAWYERS TO THE CONCEPT OF “CRIMES AGAINST HUMANITY” DURING THE SECOND WORLD WAR
Bibliographic record
Abstract
This article addresses the normative framework of the concept of “crimes against humanity” from the perspective of intellectual history, by scrutinizing legal debates of marginalized (and exiled) academic–juridical actors within the United Nations War Crimes Commission (UNWCC). Decisive for its successful implementation were two factors: the growing scale of mass violence against civilians during the Second World War, and the strong support and advocacy of “peripheral actors,” jurists forced into exile in London by the war. These jurists included representatives of smaller Allied countries from around the world, who used the commission's work to push for a codification of international law, which finally materialized during the London Conference of August 1945. This article studies the process of mediation and the emergence of legal concepts. It thereby introduces the concept of “legal flows” to highlight the different strands and older traditions of humanitarian law involved in coining new law. The experience of exile is shown to have had a significant constitutive function in the globalization of a concept (that of “crimes against humanity”).
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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.015 | 0.056 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".