A Pebble in the Shoe: Assessing the Uses of Do No Harm in International Assistance
Bibliographic record
Abstract
This paper assesses from an international law perspective the increasing use of "Do No Harm" as a principle to guide a broad array of international activities, such as state-building, human rights and climate change.Originally a medical principle derived from the Hippocratic Oath, Do No Harm's increased use has coincided with greater attention to the responsibility of international actors who, when setting out to do 'good,' have tried to ensure that activities do not cause harm or make things worse off.Do No Harm is nowhere found in binding sources, treaties or otherwise, but is invoked in connection with a range of international legal norms in a varied and inconsistent manner.The basic assumption that this paper seeks to test then is that Do No Harm is not living up to its self-stated role, serving rather to defer a series of policy or political choices concerning the nature or apportionment of various actors' responsibility.To that end, the paper describes some general features of Do No Harm's uses, followed by a more in-depth discussion of uses in humanitarian assistance, international human rights and international environmental law.That discussion reveals that Do No Harm does flag gaps in the regulation of international conduct, but does not resolve inherent trade-offs that arise when seeking to avoid harm.Those trade-offs are especially pronounced where Do No Harm's different uses overlap and risk engendering either a false sense of coherence between competing priorities, or an overly technocratic approach to risk mitigation and performing prior assessments of possible impacts of activities.The larger analysis is ultimately a call for greater conceptual clarity, when faced with the convenience offered by Do No Harm's incontrovertible veneer.
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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 | 0.063 | 0.140 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.008 | 0.054 |
| Scholarly communication | 0.019 | 0.032 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.006 | 0.006 |
| 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".