Potentiale und Perspektiven des Althochdeutschen Wörterbuchs als Thesaurus der frühdeutschen Überlieferung: Die Neufunde
Bibliographic record
Abstract
How does the long-term project Old High German Dictionary (AWB) deal with the issues of the topicality and validity of its research results over many years in view of the lively editing activity on Old High German? According to its conception, this fundamental research tool strives to be complete in terms of documentation. However, the further the dictionary progresses in print, the smaller the proportion of newly found records that will be included in the volumes to come. For the time being, any new occurrences relating to the alphabet range that has already been printed can merely be added to the document archive. On the basis of two gloss editions from different periods (Tiefenbach 1977 and Ernst/Nievergelt/Schiegg 2019), this will be quantified by way of example. Using the example of four different readings of a gloss edited over a period of 120 years, it will be shown how the respective state of knowledge in terms of edition philology is reflected in the collections of material and printed volumes (or the online version) of the dictionary. New discoveries of OHG words substantially expand our knowledge of the history of German vocabulary, as illustrated by the example of the body-part designation kunta. Finally, we will present a possible completion concept for the AWB and discuss what internal and external potentials of the AWB could perspectively be exploited in its digital presentation form. Even after being finished from A to Z, the project should be able to fulfil its role as a research centre for the vocabulary of the earliest stage of the German language.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".