Bibliographic record
Abstract
The distinguishing mark of this case is that the small island state of Antigua brought forward a WTO dispute against the United States. Instead of relying on a collective voice- or votes-based approach as part of a global solidarity campaign to defend its interests over Casino Capitalism, Antigua went one on one with the United States on its own. Such a departure from the orthodox methodology of small state diplomacy could not follow a standard script. Much has been made of the move towards the commercialization of sovereignty, whereby small states concede some components of their sovereignty via various forms of ‘flags of convenience’ in return for economic benefits (Drezner, 2001). In the Antigua-US struggles this approach was reconfigured in a manner that belied its passive or even submissive image. Ramping up the level of interaction between governments and firms, as associated with OFCs as well as shipping registries and other forms of offshore activity, Antigua and select IG firms moved towards a strategic public-private partnership — a variation of what Brian Hocking has coined ‘the privatization of diplomacy’ (Hocking, 2004) — in order to contest the United States’ stigmatization of the industry at an institutional level via the WTO. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.001 | 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 | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".