Dario Bullitta, <i>Niðrstigningar saga: Sources, Transmission, and Theology of the Old Norse “Descent into Hell”.</i> Toronto Old Norse and Icelandic Series, 11. Toronto: University of Toronto Press, 2017, pp. XIX, 203.
Bibliographic record
Abstract
Alongside the source and contextual study promised by the title, this volume also delivers an edition and the first English translation of the two primary redactions of the Old Norse version of the Descensus Christi or Harrowing of Hell translated from the medieval tradition of the Evangelium Nicodemi or Acta Pilati (for a modern Norwegian translation and parallel normalized edition of the Old Icelandic text see Odd Einar Haugen, Norrøne tekster i utval, 2nd ed., Oslo: Gyldendal, 2001 [1st ed. 1994], pp. 250–65). While the texts themselves are short and have attracted relatively little attention compared to the immense consideration afforded saga literature or Norse poetic traditions, they are nevertheless of great philological significance in the history of Old Norse-Icelandic literature and provide a window into the transmission of Latin and Christian texts. Given the amount of material covered in such few pages while retaining the fullness of the textual tradition, this study, edition, and translation is both conceptually outstanding and strong in execution. The fields of Old Norse-Icelandic language and literature and Germanic philology in a wider sense are enriched by the publication of such multipurpose volumes, whose organization should increase interest in and coverage of otherwise minor or overlooked texts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".