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Record W4380898023 · doi:10.18374/ijsm-23-1.4

HOW DO THE DIFFICULTIES OF ARMED CONFLICT AFFECT THE PERFORMANCE OF HUMANITARIAN PROJECTS? EVIDENCE FROM TERRORIST ACTS IN THE MOPTI REGION IN MALI

2023· article· en· W4380898023 on OpenAlexaff
Rodrigue Lahouri

Bibliographic record

VenueInternational Journal of Strategic Management · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTerrorismAffect (linguistics)Government (linguistics)Armed conflictCivilian populationPolitical sciencePopulationHumanitarian aidPublic relationsWork (physics)SociologyEngineeringLaw

Abstract

fetched live from OpenAlex

The implementation of humanitarian projects in areas of violent conflict is of a particular nature.Very little research has been done on this phenomenon in the existing literature.This study explores the effects of violence on the work of project managers.Through semi-structured interviews, humanitarian project managers recount their daily lives in the Mopti region of Mali, where armed groups and the government clash to the detriment of the affected civilian population.Insecurity hinders project life cycle activities.The cohabitation of humanitarian managers and security actors does not guarantee the success of projects.

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.

How this classification was reachedexpand

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.150
GPT teacher head0.357
Teacher spread0.207 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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