Germanisms in the Upper Silesian ethnolect in Poland: Commodification and Revitalization Germanismen im oberschlesischen Ethnolekt in Polen: Kommodifizierung und Revitalisierung
Bibliographic record
Abstract
In this thesis, I examine how commodification of the Upper Silesian ethnolect may contribute to the revitalization of the ethnolect. This project focuses specifically on the Germanisms, which are German loanwords in the Slavic Upper Silesian ethnolect. The Germanisms have contributed to the stigmatization of the ethnolect in the past, and they continue to be a contentious issue in the codification of the ethnolect and in the recognition of the ethnolect as a regional language by the Polish state (Hentschel, 2018). \n\tSince the change of the Polish political system in 1989, there has been an ‘ethnic awakening’ in Upper Silesia, a region in southwestern Poland. The results of the Polish National Census in 2002 and a subsequent one in 2011 show the Upper Silesians as the largest minority of the Republic of Poland with over 500,000 speakers of the Upper Silesian ethnolect. Polish legislation does not recognize Upper Silesians as an ethnic or linguistic minority (Michna, 2019). \n\tGrassroots movements in efforts to revitalize the ethnolect include a new generation of Upper Silesian speakers who use the Internet for blogging in the ethnolect or for entrepreneurial endeavors that feature the ethnolect in numerous ways. The corpus of merchandise (mainly T-shirts) analyzed in this research project was taken from an online store, the Gryfnie.com company in Upper Silesia, Poland. \n\tIn support of my thesis argument that commodification of the Upper Silesian ethnolect, as exemplified on the Gryfnie.com printed T-shirts, may contribute to the revitalization of the ethnolect, I evaluated the extent to which Germanisms are promoted on the T-shirts, which revealed that the company features Germanisms on the majority of the Gryfnie.com T-shirts. Many of these Germanisms are in the category of underutilized lexemes by current ethnolect speakers. I also examined the role of the T-shirts in the linguistic landscape and propose that in this context the T-shirts increase the visibility of the ethnolect by shifting the ethnolect from the colloquial setting of individual speakers into the public domain, which allows for an integration of the minority language across the community. Multimodal critical discourse methodology guided my examination of Upper Silesian identity construction on the T-shirts and product labels and showed that the Germanisms are used as distinct markers of Upper Silesianness, and as boundary-markers that define speakers of the ethnolect as members of an ethnic group. The same methodology revealed how the images and texts on the Gryfnie.com T-shirts for young children can aid transmission of the ethnolect by functioning similarly to picture books. Gryfnie.com T-shirts and other merchandise designed for students signal a stance toward inclusion of the ethnolect in the education environment. Enhancing the prestige of the ethnolect and conveying modernity is another strategy employed by the Gryfnie company that can aid transmission of the ethnolect to adolescents and young adults. By drawing on principles of translanguaging as a language practice, I describe how the Gryfnie.com T-shirts may support a shift in the perception of the Germanisms from stigmatized elements of the ethnolect to dynamic forms of linguistic creativity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.000 | 0.008 |
| Research integrity | 0.001 | 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".