An Assessment of Ethio-China Political Economic Relations Since 1991
Bibliographic record
Abstract
This piece of paper analyzes post-1991 Ethio-China political and economic relations by raising the following questions: What is the nature of the bilateral political and economic relations? What are the factors which enhanced the bilateral political and economic relations between Ethiopia and China? What are the arguments raised by different scholars about Ethiopia and China relations? There are a number of factors that contributed to the growth of bilateral relations. Ethiopia needs China for economic assistance; as an alternative source to the west and China’s development is generally considered as a role model for Ethiopia to follow. China also supports Ethiopia on different international issues. On the part of China, there are also several factors egging China to look towards Ethiopia especially in terms of Ethiopia’s strategic importance and market potential. Ethiopia could be a commercial launch pad for Chinese companies and China is also getting diplomatic support from Ethiopia for its policy on Taiwan among others. There are also common factors both from Ethiopia and China’s side which enhanced the bilateral relations. However, there are many arguments raised following Chinese deep engagement to Ethiopia. Among others on the economic front the bilateral relations are imbalanced; dumping of low price export; underbidding local companies and ideological differences among others. Generally, the paper agues the Ethio-Chinese relations are motivated by political and economic factors.
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".