The Art of Preserving the Dindshenchas: Investigating Scribal Alterations in 'Loch Garman, 'Lia Nothain,' and 'Berba'
Bibliographic record
Abstract
While the Dindshenchas has appeared sporadically within academia, it was not until the turn of this century that the corpus started to earn consistent interest. However, due to its size and continued presence in manuscripts, ranging from the Book of Leinster and Book of Ballymote to newer manuscripts, there are a large number of aspects in need of further investigation. This thesis will address the scribal alterations in Dindshenchas entries across multiple manuscripts, as well as to what extent this has affected the placelore material. Even though it would have been beneficial to analyse a significant amount of the Dindshenchas corpus, this project focuses on three specific Dindshenchas entries in the hopes of developing arguments and conclusions that can connect to the entire corpus. Furthermore, this thesis attempts to advocate for a closer look on the scribal alterations to the Dindshenchas, and questions why such alterations were committed in the first place. Through this analysis, it is evident that accessing the original placelore is impossible due to these alterations being introduced gradually over time. However, it is important keep in mind that the main purpose of the Dindshenchas might not have been to provide plausible and accurate entries of Irish placelore. Instead, it could have been an attempt to provide a collection of the Irish placelore, without paying attention to truthfulness, believability, or accurateness. Finally, this thesis has been written to provide a glimpse into these three Dindshenchas entries, their scribes and their preservation methods through a selection of extant manuscripts containing this complex and extraordinary Irish tradition.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".