Bibliographic record
Abstract
domen [Dung] symbolizes utter destruction, reduction, and flattening of nations, rulers, and populations to an excreted substance, cast out of the body as a symbol of revulsion. But, if seen from the point of view of an association with God’s will, it may be seen as a powerful metaphor of God’s rejection and condemnation of evil-doers. What can be worse than dogs devouring the flesh of a former Queen, Jezebel, and her carcass turned into a thing, excrement! Dung as a metaphor is part of the plant imagery used by the prophet to condemn the nation. Metaphor Theory helps to understand the four direct references to dung in Jeremiah (8:2; 9:21; 16:4; 25:33) and in II Kings (9:37). Since dung can be used as fertilizer ( zevel ) one could posit that Jeremiah prophesizes a similar fate for King Jehoiakim of Judah whose line also will end and whose corpse be exposed (Jer. 36:30), dragged out and left lying outside the gates (22:19). This will be the fate of the nation, depicted often as female, with the earth strewn with slain bodies, turned into dung (Jer. 25:33). By using the metaphor of dung, which alludes to Jezebel, associated with Jezreel, the prophet makes clear that “female” sinners deserve their fate for having betrayed the male god. The biblical Jezebel is depicted as utterly evil, however, her image has changed today, and she has been “recomposed” with a positive afterlife.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.027 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".