Disappearing Community and Preserved Identity: Indigenous Gottscheers in Slovenia
Bibliographic record
Abstract
The chapter is a case study of the indigenous Gottscheers in contemporary Slovenia. They were one of the eldest German ethnic communities outside of German and Austrian territory and the only agrarian German linguistic island on Slovenian territory after the WW1. However, their settlements and cultural landscape and heritage had been wiped out almost entirely due to the Gottscheers’ wartime and postwar emigration/eviction (mainly to the USA and Canada), the WW2, and post-war decay, marginalization, depopulation as well as village and cultural monument destruction and Slovenianization. According to the UNESCO Atlas of the World’s languages in Danger, the Gottscheer language is defined as “critically endangered”. The number of today’s Gottscheers in Slovenia is small, less than 300, or around 1000 including descendants and sympathizers. However, on the other hand, contemporary Association of Cultural Societies of the German Speaking Ethnic Communities in Slovenia as an umbrella organi¬zation of predominantly Styrian Germans aspires to acquire legal minority status for the German-speaking community in Slovenia (including Gottscheers). The aim of the chapter is therefore to detect contemporary perceptions of a marginalized and disappearing Gottscheers’ community and mechanisms to preserve and finally incorporate its identity into the Slovenian (and broader) cultural space and collective memory.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".