Wortgeografischer Wandel im Schweizerdeutschen. Sommersprossen, Küchenzwiebel und Schmetterling 70 Jahre nach dem SDS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper intends to show the importance of having linguistic instruments, principally semantic ones, for determining the meaning of words with the greatest precision and, consequently, managing to meticulously establish the different meanings of a dictionary's entry words. As an example, a new definition of the Spanish verb mezclar ('to mix') will b Since the beginning of the publication of the linguistic atlas of German-speaking Switzerland (Sprachatlas der deutschen Schweiz, SDS) in the early 1960s individual linguists collected contemporary material for comparison to investigate language change. However, due to time and money restrictions these studies were limited to small parts of the language area only. So far a description of tendencies concerning the entire Swiss German language area is missing. Based on an online-survey of 5600 informants this investigation is the first to present word geographic data covering (almost) the whole German-speaking Switzerland. Comparing GIS-maps of SDS and online data of the dialectal lexemes for freckles, onion and butterfly, language change over the last century becomes apparent, with striking convergence tendencies towards standard German, but also a Swiss German dialect expanding its range. Most of the dialect words mentioned in the SDS were preserved; some new were found. Thus, diversity of lexicon and creative language use are not endangered. Statistical analysis showed that younger speakers are more likely to deviate from the SDS. Less strong, but still significant were the influence of the parent's dialect and the duration of living in the dialect area, whereas gender had no influence.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it