Bibliographic record
Abstract
Abstract Having existed for centuries, genocide is a criminal practice that aims to destroy in whole or in part a population from a particular ethnic, racial, and religious background. The study of genocide is one that builds on historic cases of genocidal violence. Specifically, it takes on various approaches to examine genocidal crime, the intent of genocide, and how the motivation to cause physical pain and harm is knowingly implemented as a strategy of war, a tool of colonization, and a government policy of progress and modernization. Predominantly the scholarship on genocide can be summarized into three methodological approaches: (a) the theoretical that emphasizes the historic context of the crime; (b) the legal that draws from the United Nations Genocide Convention; and (c) the applied perspective that focuses on specific cases of genocide using the theoretical and legal lens. Recently, in the 21st century, genocide studies involving Indigenous populations has gained more traction as governments have been forced to recognize their own involvement in genocide, such as the forced removal of children in Canada and Australia from Indigenous families in efforts to assimilate them to the majority culture. Among this group, however, the Indigenous populations of the Americas, specifically the Indigenous women, have been further targeted for genocide more than other communities of color due to their historic relations with settler-colonial and postconquest emerging societies. The experiences of Indigenous women and their genocides involving sexual violence and coercive sterilization practices are the missing story in the genocide literature.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.028 | 0.027 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.013 |
| 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".