Bibliographic record
Abstract
Abstract While many commentators take Ezek 8:14 at face value, ancient Near Eastern parallels call this understanding into question. Both East and West Semitic sources indicate that mourning rituals for a goddess’s dead consort were carried out in state-sponsored temples that symbolized the goddess. Since this does not accord with what is known about the Jerusalem temple in the early sixth century BCE, it is probable that the visionary writer of verse 14 has projected onto the temple observances for the dying god that did not belong to it. There are indications, however, that his mourning rites were also observed in less formal settings. Women were prominent participants in these popular rituals (as they were in funeral observances in general). It is likely, therefore, that the author of verse 14 knew of mourning rites for a dead god observed in Judah outside of the temple context. Since Ezekiel indicted illegitimate cultic activities that took place throughout the nation for defiling the central sanctuary, the vision of ritual mourning for Tammuz buttressed the prophet’s claim that YHWH had decided to abandon the temple. As it is uncertain that women in Judah called the dead god “Tammuz,” the use of that divine name may come from Ezekiel.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".