Historians As Enablers? Historiography, Imperialism, and the Legitimization of Russian Aggression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This essay raises the issue of historians’ responsibility to the communities that they study. While some purported version of history has been central to the Kremlin’s justifications for Russia’s aggression against Ukraine, the region’s historians have failed to make a stand against this misuse of history. Moreover, in many instances they endorsed and disseminated the Kremlin’s narratives about Ukraine’s past and present. Aiming to explain the anti-Ukrainian biases that have become well entrenched in both Western academia and Western public opinion, this essay examines the regional subfield of area studies, to which Ukrainian studies are usually relegated, as well as the expectations and agenda of the Western-educated public. I argue that the subfield is dominated by Russian studies and frequently uncritically adopts the positions, concepts, and explanations of Russia’s imperialist ideologists. At the same time, Western public opinion, while opening up to the historical injustices committed by Western empires, still sees the world through retrograde imperial lenses. The essay also discusses in detail what happens when researchers shaped by both these trends write Ukrainian history. Looking for ways forward, I suggest rethinking the issue of intellectual responsibility and “de-imperialization” of Ukraine’s Western historiography.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it