Bibliographic record
Abstract
A Soviet national of Gagauz ethnic origin from the Moldavian SSR might have crossed borders to visit Gagauz villages in Bulgaria, Greece and Turkey. In each location the aspect(s) of brotherhood to be celebrated would have varied: a common language, religion, historical territory, shared genealogical ties, similar forenames or family names, amongst others. Today, a Moldovan national of Gagauz ethnic origin can do the same but with an altogether different positioning. The redrawing of borders and the creation of new entities after the break-up of the Soviet Union has had profound implications for the formation of Gagauz national identity, especially now that the minority status of the Gagauz has been transformed with the establishment of the Gagauz Autonomous Territory. The Gagauz population engages in cross-border travel and temporary migration to neighbouring countries alongside other Moldovan citizens, but they also travel abroad as representatives of Gagauzia/Gagauz Yeri. By looking specifically at Gagauz-Turkish encounters, I illustrate the symbolic and instrumental significance of borders and the way in which they shape the definition of Gagauz national identity (cf. Donnan and Wilson 1999).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.020 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".