Book Review: <em>Invisible Atrocities: The Aesthetic Biases of International Criminal Justice</em>
Bibliographic record
Abstract
By then I had mustered the strength to look upon misfortune with composure, to still my emotions, by then I had begun to understand the beauty of destruction…" 1 "Not even one's own pain weighs so heavy as the pain one feels with someone, for someone, a pain intensified by the imagination and prolonged by a hundred echoes." 2What role do aesthetics and emotions play in recognizing and prosecuting atrocities?Which atrocities are placed in the spotlight and which remain hidden in the shadows-obscure, unseen, and invisible?And in turn, what do the (in)visibilities mean for accountability and quests for justice?These are the questions at the heart of Randle DeFalco's new, thought-provoking book, Invisible Atrocities: The Aesthetic Biases of International Criminal Justice.The book, which is largely based on the author's observations, impressions, and analysis of existing literature and legal material, "explores what roles aesthetics play in shaping how we conceptualize what international crimes are and, imagine how they might be committed."DeFalco takes the reader on a critical 3 journey into the ways international criminal justice imagines the "unimaginable atrocities that deeply shock the conscience of humanity" and what violences (and why) escape its gaze. 4Even while Invisible Atrocities comes across as a plea to expand the scope and reach of international criminal justice, DeFalco contends that he does not aim "to advocate for the abolishment, continuation, or expansion of international criminal justice as a global project.Rather, given [his] ambivalence about the legitimacy and usefulness of international criminal law (ICL) […] [his] ambition is to contribute to a more nuanced understanding of what this body of law actually does and does not do, and perhaps more importantly, what it can and should do if it continues existing."And so he does.DeFalco, who is a law professor, presents 5 an internally-focused critique of ICL's performance; in particular, its selection of situations and
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.092 | 0.041 |
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".