Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Racialization—the processes that infuse social and political phenomena with racial identities and implications—is an assertion of power, a claim of purportedly inherent differences that has saturated modern diplomacy, order, and violence. Despite the field's consistent interest in power, international security studies in the United States largely omitted racial dynamics from decades of debates about international conflict and cooperation, nuclear proliferation, power transitions, unipolarity, civil wars, terrorism, international order, grand strategy, and other subjects. A new framework lays conceptual bedrock, links relevant literatures to major research agendas in international security, cultivates interdisciplinary dialogues, and charts promising paths to consider how overt and embedded racialization shape the study and practice of international security. A discussion of several research design challenges for integrating racialization into existing and new research agendas helps scholars reconsider how they approach questions of race and security. Beyond diversifying the professoriat itself, revealing and countering embedded biases are crucial to determine how alternative ideas have been marginalized, and, ultimately, to develop better theories.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it