The Promises and Perils of Periodization in Global History: Lessons from the Inter-War Era
Bibliographic record
Abstract
Abstract This article considers the role of periodization in global history through the lens of the inter-war era. The global turn has shifted the ‘metageographies’ of historical practice, focusing historians’ attention on the flows, mobilities and networks that connected peoples and places across the globe. Often left uninterrogated, however, are the ‘metatemporalities’ that structure historical inquiry, resulting in the perpetuation of Eurocentric definitions of historical epochs, particularly in the modern era. Periodizations are not objective or merely descriptive containers for historical events, but are themselves arguments that promote certain historical actors and dynamics from particular places, while relegating others to reactive roles, if not historiographical obscurity. The inter-war era offers a particularly compelling case study that shows how global history methodologies qualify, extend and dissolve inherited temporal frameworks. In place of singular, Eurocentric eras, polycentric global history presents the opportunity to elaborate polytemporal models that advance plural, overlapping periodizations. Aligning multiple global periodizations and becoming attuned to the rhythms they produced allows historians to reveal the particularity of historical eras.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".