Bibliographic record
Abstract
Belarusian Transnational Networks and Armed Conflict, 1921 - 1956 traces a network of nationalists who, from 1921 to 1956, worked in pursuit of Belarusian independence. They began their activism in a shattered, post-First World War Belarus, pushing for the development of Belarusian nationalism and identity. They later collaborated with the Germans during the Second World War and actively participated in violence against locals through anti-partisan campaigns and nationally driven conflict. Those in positions of power organized armed groups for a potential Belarusian fighting force. Regardless of their past, many of these individuals were later recruited by western intelligence services as anti-Soviet agents and were given resources to fund the Belarusian national cause as émigrés. This dissertation contributes to and stands out from current historiography through its focus on a particular Belarusian cast of characters that, in turn, necessitates an elongated periodization of the struggle for self-determination. The chronological elongation departs from existing literature that focuses on specific chapters of Belarusian history, usually demarcated by official periods of war. This study challenges those disparate periods and argues for their collective analysis. This work’s importance also rests on its utilization of untapped archival material coming from declassified files in the National Archives in College Park Maryland, the International Tracing Service, and Belarusian regional archives. Both the inclusion of this material and the extended periodization expose the fluidity of networks to adapt under different conditions, muddling traditional categorizations of such groups as either “anti-Polish”, “anti-German”, or “anti-Soviet”. My approach situates this study as a microhistorical work in a global context. In doing so, the research contributes to the field of Russian and East European Studies by underscoring the need to expand our spatial and temporal understanding of the region. The central historical stage is not geographically constrained to only this part of the world but spans several continents. Focusing on Belarusian nationalists, imbedded within larger forces of war and violence, produces a study that is relevant both in its local and transnational historical value.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".