Are Baklava and Burgers Enough? Seeking Cosmopolitanism through Culinary Practices, Food, and Food Cultures in Perikles Monioudis’s <i>Land</i> and Yadé Kara’s <i>Cafe Cyprus</i>
Bibliographic record
Abstract
Recent theories of cosmopolitanism address how individuals grapple on the everyday level with the intermingling of cultures and the experience of borders in the current era of globalization. In this article, close readings of the novels Land (2007) by Perikles Monioudis and Cafe Cyprus (2008) by Yadé Kara investigate the ways in which the depicted food cultures and practices, food pathways, and consumption tendencies, as well as the use of alimentary metaphors, problematize extant and negotiate new notions of cosmopolitanism as well as posit everyday acts of cosmopolitan agency as a means to cultivate a nascent sense of transnational community and belonging, albeit one that is ephemeral and fraught with conflict, fissures, and failure. I argue that the notions of cosmopolitanism and “cosmopolitan borderwork” forwarded in these texts appeal for the recognition of everyday practices, modes of consciousness, and forms of transnational affiliation tied to the sensory experiences provided by food in order to inform more ethical practices of cosmopolitanism in the twenty-first century.
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.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".