Bibliographic record
Abstract
This book seeks to trace the appropriation of a particular “Old Testament pseudepigraphon” – the Book of Jubilees – in early Christian sources from the New Testament (NT) to Hippolytus (and beyond). More specifically, our study focuses on the reception of Jubilees 8–9, an expansion on the so-called Table of Nations in Genesis 10 (1 Chronicles 1). There are three primary motivations for undertaking such a study at this particular time. First, my previous work on the Table of Nations tradition has led me to the conclusion that Jubilees 8–9 had a powerful influence on geographical conceptions found not only in Second-Temple Jewish sources but also in early Christian writings. In order further to articulate and substantiate this thesis, the present study delves more thoroughly than before into some of the important primary source material. For instance, our study gives greater scope to a Hellenistic epigram that opens up the possibility of Jewish cartographic activity in the Second-Temple period (Chapter 1). The study also augments my previous work by reconsidering the relationship of Jubilees 8–9 both to the lost “Book of Noah” and to other writings of the Second-Temple period (Chapter 2). The study greatly expands our earlier discussion on the geography of Luke-Acts (Chapter 3) and penetrates more deeply into early Christian literature outside the NT (Chapters 4-6). Finally, the study ventures a foray into the medieval mappaemundi as possibly our earliest extant cartographic remains of the Jubilees 8–9 tradition (Chapter 7).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.444 | 0.289 |
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".