Serbian Queer Identities in Diaspora in Canada and the United States: Challenging Theories of “Balkan Ethnonationalism”
Bibliographic record
Abstract
Western social scientists and political observers have depicted Serbia, and former socialist countries in the so-called Balkan region covering Southeastern and Southwestern Europe, as embodiments of violent ethnic nationalisms (Dyrstad, 2012; Gordy, 2016). This study investigates the existence of ethnonationalism among members of the queer Serbian diaspora in Canada and the United States, using cultural and social theories of intersectionality, fluidity, and ever shifting identifications, as well as 15 personal interviews with queer Serbs who immigrated to Canada and to the United States between the 1990s and 2000s. In so doing, this study highlights the complexity and liquidity of Serbian queer identifications and the active ways in which these identity formations reflect forms of social privilege, yet also sexual, economic, and cultural marginality. Serbian queer immigrant notions of self, Other, “nation,” and “homeland” present negotiations of this privilege and marginality amid hegemonic and deeply homophobic Canadian and American societies; spaces already hostile to migrants who defy the normative cultural foundations of capitalism, heterosexuality, and Western modernity steeped in celebrations of civilization associated with “Europe” wherein Serbia and other Balkan societies imagined as “ethno-nationalistic,” and therefore “violent and backward,” do not really belong. The interviews illuminate the violent ways in which the Serbian state and society also discriminate against queer and non-normative members of the nation, further complicating and layering how queer Serbs in diaspora perceive home, nation, and express or do not express modes of nationalism. The analysis draws from critical realism, realist ontology, and constructivist epistemology to uncover underlying power dynamics and social structures giving shape to these Serbian queer identity formations in diaspora. Ultimately, this research contributes to deeper and better understanding of queer and immigrant identitites in Canada and the United States adding new knowledge especially to literatures on queer nationalisms in North America, as well as theories of nationalism across political science, history, and area studies focused on the geopolitical region called the Balkans.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.041 | 0.021 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".