A Sea Change:Problematizing the “Gray Zone” in the South China Sea
Bibliographic record
Abstract
Throughout discussions of the geopolitical conflict in the South China Sea (SCS), analysts tend to shy away from using the term "armed conflict" to describe actions taken within the maritime domain.Analysts have relegated such actions to the "gray zone"; a legal ambiguity between the threshold reaching an armed attack and the threshold for reaching an armed conflict.This essay argues that the law of armed conflict (LOAC, commonly referred to as international humanitarian law or IHL) actively regulates more actions in the SCS than some legal analysts let on, and that the LOAC is best suited to regulate actions over that of strictly maritime law.Through an analysis of various incidents between claimants in the SCS, it is revealed that the LOAC effectively lowers the threshold for reaching a state of armed conflict, allowing for more firm arbitrations to be made on the basis of constituting armed attacks rising to the level of armed conflict, as well as determining contributions to an armed conflict.
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 | 0.002 | 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 | 0.020 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".