Unwürde, Lubij, Dažin, Stwěšin und andere Namen altsorbischer Herkunft. Miszellanea und manches Systemhafte (Teil II)
Bibliographic record
Abstract
Unwürde, Lubij, Dažin, Stwěšin and Other Names of Old Sorbian origin. Miscellanea and Some Arguments of a Systemic Nature (Part II) Onomastic analysis should interpret the entire development of a name; it should not be limited to the recent form nor to the oldest one, for all forms have their own causal background (Šmilauer). It seems that in the modern literature about Lusatian place names this rule has not always been sufficiently obeyed. So, in a number of cases, new Sorbian forms have been explained as being caused by the influence of Germanized ones, although an inner Sorbian development could well have led to a given later state. Furthermore, a satisfactory solution cannot always be provided by simply “making a calculation”, starting either from the oldest form and moving forward, or going back from the latest one. In this sense, in the 2nd section alternative interpretations of Dažin and Dźěžnikecy, Njeznarowy, Łuwoćicy, Lutobč, Radska, Zemicy and Tumicy are proposed. Attention is paid to some names whose history includes an unexplained disappearance or the appearance of a particular sequence. Certain aspects of Njeswačidło and the Coswig names were re-examined. An interesting solution was found in the case of the “mysterious” name Stwěšin, which suggests that it is derived from a hypocorism of an older Slavonic borrowing of Stephanus.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".