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South Sudanese Crisis and Its Foreign Intervention, 2013-2021

2022· article· en· W4310848149 on OpenAlexaboutno aff
Ekanem Ekanem Asukwo

Bibliographic record

VenueSouth Asian Research Journal of Humanities and Social Sciences · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsDisarmamentPolitical scienceHumanitarian crisisPoliticsIntervention (counseling)Economic growthLawMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the dynamics of South Sudanese crisis from 2013 to 2021. Descriptive research design that anchored on the judgmental sampling technique was adopted. The secondary sources (books, journal articles, conference papers, internet materials and monographs) were sourced from Nigerian libraries and internet, subjected to content analysis, before qualitatively analyzed for the study. Findings revealed that political exclusion, proliferation of small arms and light weapons, corruption and weak institutions triggered grievances that led to December 2013 South Sudanese crisis. The crisis had impacted negatively on security, humanitarian needs, human rights, as well as economy. United Nations Mission in South Sudan, Inter Governmental Authority on Development, African Union Mission in South Sudan, United States, Canada, Uganda, Sudan, Kenya, Ethiopia and Eritrea had intervened. Though these findings have deepened the understanding of Group theory, the fear of South Sudanese crisis reoccurring immediately after general election in 2024 is looming. The study the recommends, rotational presidency, devolution of power, mental disarmament and development assistance to avert the incoming crisis.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.105
GPT teacher head0.384
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2022
Admission routes1
Has abstractyes

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