The political imaginary of the protection of civilians (PoC) : the tension between militarism and humanitarianism in NATO and UN policy
Bibliographic record
Abstract
As a relatively new concept, Protection of Civilians (PoC) has only recently begun to be labelled as an explicit objective of interventions involving armed conflict.With its central focus being the protection of the lives of those not party to hostilities, PoC establishes itself as a fundamentally humanitarian concept.However, challenges to this humanitarian foundation emerge as PoC is coupled with interventions comprised of military components, i.e. militarism.This essay endeavors to shed light on the tension between humanitarianism and militarism within the concept of, and policies on, PoC.It advances the argument that these aspects of armed conflict and PoC clash against one another, each striving for prioritization in policies on protection.Moreover, it argues that militarism often takes precedence over humanitarian approaches to civilian protection through the dominance of the use of force.This essay employs relevant literature on PoC and international intervention to offer an examination of the implications that evolve out of the dynamic between militarism and humanitarianism.This examination is pursued through a case study of the PoC policies of the North Atlantic Treaty Organization (NATO) and the United Nations (UN).The case study brings to light the challenges posed to PoC's humanitarian credentials, which are instigated by the political imaginaries of PoC that are centered on the use of force.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".