Bibliographic record
Abstract
Famine remains one of the major causes of deaths and displacements in the Sub-Saharan African countries where people have continuously been compelled to cross international borders in search of livelihood securities. There is no question that the continent has been exposed to erratic rainfalls, crop failures and droughts, but contemporary famine has less to do with natural-related crop failures and much to do with poor governance. The author argues that state’s premeditated action, inaction and incompetency to respond to insecurity and threats are largely responsible for African famines. Due to historical misperception of African famine and oversimplification of refugees’ motives from Africa, however, food-based persecution has not been a common subject of research. Besides, the absence of drought does not necessary mean the absence of famine either, because the aforementioned factors frequently cause it to happen even in the middle of plenty. Therefore, the purpose of this paper is to explore how government’s action or inaction can lead to famine in the absence or presence of drought which in return forces people to escape from drastically deteriorating conditions of existence by flight. The goal of this paper is mainly to challenge the common perception that famine as being the drought-induced outcome of humanitarian crisis in Africa and refugees as being victims of the natural circumstance. Thus, this paper argues that a government that deprives its citizens of the basic necessity such as the right to food is as dangerous as the one that persecutes its citizens on the five Convention grounds. Hence, taking Eritrea as a case example, this article discusses chronic food insecurity and mass starvation as a state-induced disaster, which I believe should be considered a crime against humanity under the Rome Statute of the International Criminal Court.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".