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Record W3200665806 · doi:10.1093/jogss/ogab024

Compromising Aid to Protect International Staff: The Politics of Humanitarian Threat Perception after the Arab Uprisings

2021· article· en· W3200665806 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Global Security Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaFulbright Canada
KeywordsPerceptionPoliticsPolitical scienceHumanitarian aidInternational relationsInternational communityPublic relationsLawPsychology

Abstract

fetched live from OpenAlex

Abstract Scholars expect operational compromises by humanitarian organizations to follow attacks on aid workers. However, in response to the War in Syria, organizations compromised aid and adopted clandestine, cross-border, remote management, and conflict-actor aligned approaches, which best protected international aid workers. This was despite declining rates of attack against them, relative to their national staff counterparts. This article asks why international aid workers were withdrawn and aid was compromised in the wake of the Arab Uprisings by traditional risk-taking organizations: Médecins Sans Frontières (MSF) and the International Committee of the Red Cross (ICRC). Drawing on political ethnography and interviews with aid workers, I show that shocking violent events, everyday insecurity, and changes in the nature of threat have significant effect on threat perception and explain compromises where rates of attack do not. This paper offers a picture of the micro- and field-level foundations of organizational threat perception and decisions about whose security matters.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.365
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it