Theoretical Synthesis in IR: Possibilities and Limits (SWP 6)
Bibliographic record
Abstract
This is a draft chapter for Sage Handbook of International Relations, 2nd Edition, which offers a critical assessment of bridge building and pluralism in contemporary international-relations (IR) theory. I begin by placing recent moves towards theoretical synthesis in context, asking why one saw an upsurge of interest in bridge-building only beginning in the mid-1990s. Then I assess these efforts in three areas – international institutions, normative theory, and studies of civil war – in each case, detailing how and to what extent theoretical pluralism has come to define a particular subfield. I argue that contemporary IR does look different, and better, thanks to synthesis and bridge building. In conclusion I note two challenges – theoretical cumulation and meta-theory. These, I argue, should be at the heart of a reinvigorated research program on synthesis, one where theory is taken seriously and epistemological divides are transgressed.
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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 | 0.029 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".