Bibliographic record
Abstract
The current surge of displaced and trafficked children, child soldiers, and child refugees rekindles the virtually dead letter of the Genocide Convention prohibition on transferring children of one group to another. This book focuses on the gap between genocide as a legal term and genocidal forcible child transfer as a catastrophic experience that disrupts a group’s continuity. It probes the Genocide Convention’s boundaries and draws attention to the diverse, yet highly similar, patterns of forcible child transfers cases such as colonial genocide in the US, Canada, and Australia, Jewish-Yemeni immigrants in Israel, children of Republican parents during the Spanish Civil War and its aftermath, and Operation Peter Pan in Cuba. The analysis highlights the consequences of the under-inclusive protection granted only to four groups. Ruth Amir argues effectively for the need to add an Amending Protocol to the Genocide Convention to protect from forcible transfer to children of any identifiable group of persons perpetrated with the intent to destroy the group as such. This proposed provision together with Communications and Rapid Inquiry Procedures will highlight the gravity of forcible child transfers and contribute to the prevention and punishment of genocide.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".