Introduction: claiming the international beyond IR
Bibliographic record
Abstract
Claiming the International was conceived as the third in a sequence of edited books growing out of a conversation that began at the International Studies Association (ISA) meeting in Montreal in 2004. The conversation traveled for a while under the label, “Geocultural Epistemologies and IR” and morphed into the Routledge book series, “Worlding Beyond the West.” The series promises to focus on the issue of domination of the discipline by the West, explore the role of geocultural factors in determining how knowledge of world politics is produced, and seek out alternative ways of thinking about the “international.” The first two books of both the series and the original trilogy-International Relations Scholarship Around the World (Tickner and Waever 2009) and Thinking International Relations Differently (Tickner and Blaney 2012)—explore the ways in which the field of International Relations (IR) has globalized via a set of boundary-drawing practices that inform particular modes of worlding and knowledge. The language of production is used intentionally (as opposed to diffusion) in order to highlight the geocultural conditions of possibility of IR as a globalized discipline, as well as the localized contexts beyond the West in which it is received, adopted, adapted, and/or rejected. In other words, the books have been attentive to the situatedness of knowledge and experience.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.035 | 0.008 |
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".