THE MAP OF MULTILATERAL TREATY‐MAKING 1600–2000: A CONTRIBUTION TO THE HISTORICAL GEOGRAPHY OF DIPLOMACY
Bibliographic record
Abstract
ABSTRACT The paper describes and analyses the successive geographical distributions of places where multilateral treaties have been signed over the life course of the state system. A large proportion of all negotiations occurred in just a few places and the collection of most frequently selected places shows considerable continuity over time. Treaty‐making emerges as more of a secular trend than a cyclical pulse, being insignificantly impacted by economic cycles, and inconsistently impacted by hegemonic cycles. The work presents a measure of specialisation that helps to identify types of central venues in the multilateral treaty‐making system. The actual selection of specific venues suggests functional and political considerations to have been most important. The sustained preference for national political centres expresses the importance of such considerations, while the actual choice of a venue in a specific case can be highly contingent.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".