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Record W2795886344 · doi:10.1080/08865655.2018.1457975

Terrorism in the Lake Chad Region: Integration of Refugees and Internally Displaced Persons

2018· article· en· W2795886344 on OpenAlexvenueno aff
Oyewole Simon Oginni, Maxwell Peprah Opoku, Beatrice Atim Alupo

Bibliographic record

VenueJournal of Borderlands Studies · 2018
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeInternally displaced personLivelihoodTerrorismPolitical scienceFocus groupEconomic growthDisplaced personIdentity (music)GeographyDevelopment economicsSocioeconomicsSociologyAgriculture

Abstract

fetched live from OpenAlex

The Lake Chad region is an intersection of four countries, namely Cameroon, Chad, Nigeria, and Niger, and has been a battleground of terrorism in recent years. While much is known about the devastating impact of the activities of Boko Haram, there is a dearth of empirical research on how individuals displaced by terrorism in the Lake Chad region have been integrated into new communities. Thus, the aim of this study was to explore the experiences of refugees and internally displaced persons (IDPs) regarding their integration into new communities in the Lake Chad region. The study adopted a qualitative design, that is, interviews and focus group discussions, to interact with participants from nine communities in Cameroon and Nigeria. Sixty-seven participants consisting of refugees, IDPs, host community leaders, and camp leaders were recruited to share their experiences. The study found similarities in the experiences of refugees and IDPs. Specifically, the study found that common identity (i.e. common culture and languages) enhanced social connection, safety, and integration of the refugees and IDPs into new communities. However, little has been done in terms of job creation, to enable refugees to have a source of livelihood, access to property, and essential services. The study has implications for policy-making in terms of governments in the Lake Chad region capitalizing on common identity and developing employable programs which will revitalize the economy of the region.

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)0.000
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 score0.645
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.042
GPT teacher head0.380
Teacher spread0.338 · 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

Citations20
Published2018
Admission routes1
Has abstractyes

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