You Shall Call Me Yahweh: The How and Why El Came to be Known as Yahweh (Exod 3:1-15)
Bibliographic record
Abstract
You shall Call Me Yahweh: The How and Why El Came to be Known as Yahweh (Exod 3:1-15)MA -Near & Middle Eastern Civilizations 2023 Thandazani Mhlanga Department of Near and Middle Eastern Civilizations University of Toronto Moses’s encounter with Yahweh at Horeb and the corresponding exodus have arguably attracted academic debate for a longer period than most biblical passages. In this thesis, it is the author’s intent to conduct a nuanced rhetorical criticism of Exodus 3:1-15 that considers form criticism and the oral tradition undergirding the text. A new all-encompassing interpretive system is also suggested and utilized for the purposes of sharpening our interpretive precision and enhancing our sensitivity and comprehension of the text. Through this nuanced multi-layered critical approach, it becomes evident that the story of Moses’s encounter with El, the God of Your fathers, in Exodus 3:1-15, is an etiological myth of Yahweh as the innate character of El. Furthermore, the corresponding Sitz im Leben of this switch from El to Yahweh brings to light the often elusive and, consequently, ignored relationship between the story and the storyteller.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".