The FG Hemisphere Case in Hong Kong: China's Africa Policy in the Courts of Its First Special Administrative Region
Bibliographic record
Abstract
In the FG Hemisphere case, Hong Kong courts were faced with a decision on whether to enforce an arbitral award against a sovereign state, the Democratic Republic of the Congo, despite the objections of the Central Government of the People’s Republic of China. The central government argued that the executive, not the courts, should have the final word on whether Hong Kong should adopt an absolute or restrictive approach to sovereign immunity. The Hong Kong government also argued that, under the Hong Kong Basic Law, the Hong Kong Court of Final Appeal (CFA) had no power to decide, but should submit the issue to the National People’s Congress Standing Committee. In an unprecedented decision, the CFA agreed to submit the case.Within this debate lay fundamental differences in how to understand the nature of law and China’s sovereignty over Hong Kong under the “one country, two systems” regime. This Article analyses this debate over the appropriate rules of recognition and highlights differences in approach among Hong Kong judges, and between the judges and Mainland authorities. It argues that the theory of executive power finally articulated by a majority of the CFA is fundamentally different from the theories advanced in the United States or the United Kingdom, which the CFA sought to use as precedent. This Article then discusses possible repercussions of the case.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| 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".