Contesting National Identities in an Ethnically Homogeneous State: The Case of Armenian Democratization
Bibliographic record
Abstract
This study of recent Armenian identity politics raises two intertwined theoretical questions. First, it asks whether there can be contesting national identities in an ethnically homogeneous state. Second, following theoretical propositions of liberal nationalism it explores whether identity contestation in an ethnically homogeneous state affects political trust, perceptions of social justice, and democratic attitudes.\nMy research focuses on the analysis of politically relevant national identity issues: Genocide and Relations with Turkey, War in Mountainous Karabagh and Possible Solutions, and Dual Citizenship for Diaspora, and the ways these are perceived by the public and political elites in the Armenian Republic. To explore my research questions, I conducted a public opinion survey, employed a quantitative content analysis of electoral platforms and newspapers, and conducted a qualitative analysis of legislative and constitutional provisions.\nResults of this study illustrate that Armenian national identity--considered by many as uncontested because of shared ethno-cultural features, and the Soviet legacy--contains conflicting criteria for assessing tragic memory, territorial aspirations, and belonging to a nation-state. These findings challenge the conventional assumption prevalent in theories of nationalism according to which shared ethno-cultural attributes of a homogeneous community so powerfully shape its collective identity that no politically significant internal disagreements could arise in an ethnically homogeneous state.\nContrary to this assumption, findings reveal that contrasting ways of remembering, imagining political boundaries, and defining belongingness to a political community are not the province of ethnically heterogeneous states alone. Persistent identity contestation also challenges the Soviet legacy hypothesis, according to which Armenia inherited a single and institutionalized ethnic type of identity from its Soviet past. Results suggest that Armenian national identity has not been as deeply institutionalized along ethnic lines as it has been argued so far.\nFinally, results suggest that studies explaining political trust, social justice, and democratic attitudes not only should consider national identity but also whether that identity is shared by the members of a political community. Essentially, findings indicate that the type of shared identity is central for assessing its instrumental and ethical significance and underscore the critical importance of distinguishing between liberal and illiberal forms of national identity.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".