Canada, the International Criminal Court, and the intersection of international politics and finances
Bibliographic record
Abstract
In 2018, Prime Minister Trudeau made two announcements regarding the International Criminal Court, both, it seems, aimed at reinforcing Canada’s claim of human rights promotion and multilateralism: Canada declared Myanmar’s actions against the Rohingya people genocide and urged the United Nations Security Council to refer the situation to the International Criminal Court, and it joined a collective referral of the Venezuela situation to the Court. As public measures of support, these are positive developments for the International Criminal Court, which has been suffering poor public relations and challenges to its legitimacy. However, Canada could do more by better supporting the financial viability of the Court. Currently, it aims to increase the Court’s workload without supporting an increased budget, as reflected in Canada’s involvement at the December 2018 Assembly of States Parties meeting. A seemingly sure way to undermine the International Criminal Court would be to add to its workload without ensuring it has the financial resources to do the work.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.025 | 0.025 |
| Scholarly communication | 0.022 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.017 | 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".