Bibliographic record
Abstract
This article explores the crime of genocide in connectivity to groups defined by gender. Its aim is to investigate whether including groups defined by gender as a protected group in the Genocide Convention appears legally plausible. It begins by probing the historical origins of the concept of genocide. This exposition emanates into an analytical examination of the rationale of protecting human groups in international criminal law. Against this background, the article advocates an understanding of the crime of genocide as a rights-implementing institute. Subsequently, it employs an ejusdem generis analysis to assess whether groups defined by gender are coherent with the current canon of the protected groups, and if similar treatment thereby can be warranted. It then turns to examine other international law instruments, to expose that none of these are suitable proxies in dealing with gender-specific genocides. From this perspective, the article suggests that the content of the crime of genocide is not determinate, but rather emerges as a battlefield for hegemonic interests. Hence, it is easily discernible that the way in which the current construction of the protected groups in the Genocide Convention relates to gender groups reflects a deliberate choice. The article concludes with asserting that the choice represents a lacuna in international criminal law that in the end compromises the legitimacy of the crime of genocide, since the personal scope of the crime of genocide risks being in discord with current social and political trajectories.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".