Contaminating National Identity Through Intercultural Intimacy: (Im)purity and the Pandemic
Bibliographic record
Abstract
This paper brings together the threads of contagion, intimacy, and national identity in an exploration of border crossings. Framed through the COVID-19 pandemic and the rise of vaccine nationalism, we interrogate the discourse of contagion and impurity and trace the ways it has been used by self-interested elites to advance ethnonational, exclusivist agendas. Using the authors’ relationship as a jumping off point for critical and cultural analysis, we use intimacy, affect, and illness as hinges between bodies, identities, and geographies. We argue that non-traditional, queer, cross-cultural relationships and encounters are sites through which to interrogate the violence of borders and to subvert the exclusion and hierarchy inherent to nationalism as a political project. We offer an experimental model for performing political and cultural research across disciplinary boundaries, advancing knowledge dissemination between and across fields.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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".