Formal or Informal, Legal or Illegal: The Ambiguous Nature of Cross-border Livestock Trade in the Horn of Africa
Why this work is in the frame
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Bibliographic record
Abstract
In this article, we address cross-border trade from the perspectives of state institutions and their agents, on the one hand, and private merchants and pastoralists, on the other. It will be shown that at times their agendas strongly conflict, but in other situations workable accommodations and policy interpretations are found even while acknowledging the illegality of the actions. Because of the extensive border zones in the Horn with few custom posts and banking facilities, the state often has no recourse but to turn a “blind eye” to cross-border trade. Throughout the paper, it is shown how vastly different border policies and international relationships among neighboring countries (i.e. Ethiopia, Kenya, and Somalia) in the region challenge generalizations about informality and cross-border trade. In the conclusion we assess recent attempts by government authorities to coerce the trade into formal channels, but with minimal success.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it