Die Neißeprovinz als Kleingau?: eine Erwiderung zum Beitrag von Walter Wenzelüber „Die provincia Nice“
Bibliographic record
Abstract
A Small Slavonic Region called Nice? A reply to Walter Wenzel´s paper about “The provincia Nice”. – The present essay on the early-medieval settlement areas at the River Neiße/Nysa Łużycka in Lower Lusatia, deals with the issue of the provincia Nice, a name which appears among the toponyms of the region and has been the subject of a joined study together with Ernst Eichler. The only written evidence documenting Nice is the chronicle of Thietmar of Merseburg. Its localization is unknown, and all attempts to localize it remained as yet unconvincing. The proposition of the aforementioned study is, that this name may be referring to the only known settlement area at the lower Neiße river which went by the name Selpuli, thus assuming that Nice was effectively a quasi- synonym for Selpuli. Walter Wenzel contradicted this and localized Nice in a smaller area around the present-day town of Forst. For his reconstruction he used place names, archaeological findings and personal names. In this article all of his arguments are revisited (parts 2–4) and, as a result it is found, that not all of them can be accounted for as indicative of an early medieval settlement. Therefore Wenzel’s theory yields no evidence which would invalidate the proposition that Nice geographically coincides with Selpuli. Finally (parts 5 and 6) this assumption is discussed in the context of settlement geography, including a short analysis about the use of the terms pagus and provincia in Thietmars chronicle.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".