Bibliographic record
Abstract
This thesis explores the development of angelic mediation in Second Temple Judaism. Within this broader topic, I focus on a specific type or group of angelic beings who are given a variety of different names by scholars. They are often described using the following titles: an angelus interpres, an interpreting angel, a heavenly tour guide or an otherworldly mediator. What distinguishes these angels from previous angelic beings is that they engage in dialogue with a human as they mediate divine revelation. The first explicit mention of such an angel occurs in Zech 1:9 where he is identified as המלאכ הדבר בי “the angel who spoke with me.” Similar angelic beings also feature prominently in various Second Temple texts who assume the roles of interpreters, guides and/or intercessors. In each case, the angelic figure and the human are continually engaged in a dialogue featuring primarily a question-and-answer format. This thesis seeks to delineate the nature and function of these angelic figures and their use especially as they develop in the earliest texts of Zech 1-8, 1 En. 1-36 and Dan 7-12. It concludes that one cannot speak of a homogenous tradition of angelic mediation but one which is continually adapting over time. Although broad lines of continuity are present between the three books, these angelic mediators are not stock characters that are identical in function. Instead I argue that each text brings its own adaptations and idiosyncrasies to these existing traditions generating new presentations of angelic mediation.
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 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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".