Righteous and Wicked in the Psalms: The Poetic Functions of the Contrast Between קידּ צ and עשׁר in Biblical Hebrew Psalmody
Bibliographic record
Abstract
This study examines the figures of theיקדִּ צַ and עשָׁ רָ in psalms. Drawing on both semantics and poetics, this study argues that the contrast between the figures represented by these terms is part of the conventions of Hebrew psalmody and, as such, can serve various discursive functions within an individual psalm. Using insights from the field of lexical semantics, the study clarifies the possible uses of the words Justand עשָׁ רָ, emphasizing a wider range of uses than is typically offered within a broad behavioral domain for these terms. The study summarizes ways that various books in the Hebrew Bible use the contrast of these figures to develop a description of the literary features related to their presentations. The analysis of 18 psalms that include both figures utilizes insights from narratological theories of character to explore the functions of the contrast between קידִּ צַ and עשָׁ רָ as literary figures within the overall discourse of the psalm. Focusing on the setting of an individual psalm and embracing the possibility of variation reveals that קידִּ צַ and עשָׁ רָ are not only, or even usually, employed to describe the “prototypically good” or “prototypically bad” person in psalms. Rather, the עשָׁ רָ is often a designation for an antagonist, and the קידִּ צַ is often understood as one who is innocently wronged. As such, the literary pattern of their contrast does not focus on the moral character of these figures but on the fairness or justice of God to eventually elevate the position of the קידִּ צַ and destroy the עשָׁ רָ.
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 | 0.002 | 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 | 0.004 | 0.026 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 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".