‘We became refuse and rubbish’: Violence, filth, and rehumanization after exile
Bibliographic record
Abstract
While frameworks of purity and impurity were widespread in ancient West Asia and well known before the exile, many exilic and postexilic sources focalize purity concerns. This article will explore the connection between ancient West Asian texts associating or equating conquered groups with filth and disgust-eliciting substances and the focus on impurity-removal that is so obtrusive in post-exilic biblical sources. I will argue that the rituals of purification detailed in the priestly texts of the Pentateuch constituted practices of rehumanization, seeking to alleviate the deep-seated sense of filth and impurity that a variety of texts from the exilic and post-exilic eras so clearly exhibit. These priestly texts arguably offered to Judeans both purification and a path to healing from the dehumanizing violence suffered by earlier generations, violence leaving after-effects still felt by postexilic communities, as various early postexilic texts demonstrate.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.030 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".