Beyond the Protective Effect: Towards a Theory of Harm for Information Communication Technologies in Mass Atrocity Response
Bibliographic record
Abstract
Information Communication Technologies (ICTs) are now being employed as a standard part of mass atrocity response, evidence collection, and research by non-governmental organizations, governments, and the private sector. Deployment of these tools and techniques occur for a variety of stated reasons, most notably the ostensible goal of “protecting” vulnerable populations. However, these often experimental applications of ICTs and digital data are occurring in the absence of agreed normative frameworks and accepted theory to guide their ethical and responsible use. This article surveys the current state-of-the-art of ICT use in mass atrocity response and research to identify harms and hazards inherent in the use of ICT-centric approaches in mass atrocity producing environments. The article proposes an initial theory of harm for evaluating the potential risks and impacts of these applications as a critical component of developing ethical standards for the responsible use of ICTs in the mass atrocity response context.
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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 | 0.022 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.007 | 0.085 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".