Critical Reflections on <i>MARO</i>: The View from Argentina
Bibliographic record
Abstract
The following commentary aims to analyze the main characteristics of intervention described in MARO: Mass Atrocity Response Operations; A Military Planning Handbook and to also provide a legal and historical context in which to address that work. In other words, we believe that in order for the inner value of MARO to be assessed, the handbook should be contextualized with the history of American intervention and several aspects of international law. Follow this and additional works at: http://scholarcommons.usf.edu/gsp This Article is brought to you for free and open access by the Tampa Library at Scholar Commons. It has been accepted for inclusion in Genocide Studies and Prevention: An International Journal by an authorized administrator of Scholar Commons. For more information, please contact scholarcommons@usf.edu. Recommended Citation Hairabedian, Federico Gaitan and Papazian, Alexis (2011) Reflections on MARO: The View from Argentina, Genocide Studies and Prevention: An International Journal: Vol. 6: Iss. 1: Article 6. Available at: http://scholarcommons.usf.edu/gsp/vol6/iss1/6 Critical Reflections on MARO: The View from Argentina Federico Gaitan Hairabedian University of Buenos Aires and Luisa Hairabedian Foundation Alexis Papazian University of Buenos Aires, CONICET, and Luisa Hairabedian Foundation
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.026 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.015 | 0.034 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".