Easy tools to get to grips with linguistic variation in the manuscripts of Njáls saga.
Bibliographic record
Abstract
The project "The Variance of Njáls saga" examines variation in the sixty-three medieval and post-medieval manuscripts of Njáls saga from a linguistic, philological, and literary perspective. This saga is the most extensive of the Icelandic family sagas and is thought to have been composed around 1280. The following article describes methods used in the project to identify synchronic variation at a linguistic level in the fourteenth century manuscripts of the saga, and aspects of an analysis of the stemmatic relationship between manuscripts. In both fields the development of computer-based approaches has advanced notably in the last few years. However, affordable solutions customised for end-users are still lacking. The project therefore focuses on easy tools that can be applied in a short-term project with limited financial and human resources. The manuscripts are transcribed according to the conventions of MENOTA (Medieval Nordic Text Archive) in TEI-XML; a segmentation allowing for an identification of corresponding contents is added; linguistic features relevant for an examination of variation are tagged; and structures relevant for a comparison are displayed for further analysis with the help of XSLT-style sheets. The article discusses challenges that lie in the peculiarities of medieval writing (non-standardised orthography, abbreviations) and tries to outline practicable solutions. Initial results of comparisons of manuscripts based on this approach show variation not only in the semantic domain (substitution of words), but also in the syntactic domain (change of word order, usage of different syntactical constructions).
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.
How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".