Rural Displacement and Its Implications on Livelihoods and Food Insecurity: The Case of Inter-Riverine Communities in Somalia
Bibliographic record
Abstract
This study investigates the phenomenon of forced displacement in Somalia over the past few decades and its implications for the livelihoods and food security of IDP communities. Employing a mixed-method approach, the study draws on various theories to interpret the complex dynamics underlying forced displacement and the subsequent loss of livelihoods. The findings reveal that the drivers of displacement have exhibited variation across different periods, encompassing conflicts, droughts, food scarcity, and political intricacies. Notably, the displacement experienced by inter-riverine communities primarily stems from weak institutions, intensified resource competition, disputes over fertile agricultural land, and conflict and food scarcity. This displacement has resulted in a rapid increase in urban populations and socio-economic crises. Primary data substantiates the severe socio-economic challenges faced by displaced individuals. Such historical perspectives and empirical evidence allow policymakers and stakeholders to better comprehend the multifaceted challenges confronting Somalia. The study underscores the agricultural implications of forced displacement, emphasizing the importance of targeted interventions to revitalize agricultural systems, resolve land disputes, facilitate access to vital resources, and enhance the livelihood conditions of affected communities within Somalia and in similar contexts elsewhere.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| 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".