First Attempts and First Principles
Bibliographic record
Abstract
This introductory chapter includes analysis of the earliest versions of Virgil: in eleventh-century Ireland, in the Roman d’Enéas and in Middle High German. It explains how I chose to organize discussion of the translation history of Virgil in the Western tradition. I explain the chronological, geographical and linguistic scope of the book and discuss the relevance of translation theory and reception theory to the project. I account for the organization of the book by considering what it might have been (and is not) as well as what it is; I include summaries of the ten following chapters along with indications of the major and minor translations tackled in each. Because the book is composed of numerous case studies, I close by facing the hermeneutic challenge of how to rise above the case study and by indicating the interpretative gains of this study and ways in which it opens up further avenues for exploration by other scholars.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".