Bibliographic record
Abstract
In a 1981 interview, Morrison told Charles Ruas that "the Bible wasn't part of my reading, it was part of my life" (97). In her use of structure, language, and concepts~~~her use of metaphor, repetition, and reiteration~~~the Bible resonates throughout Toni Morrison's novel, Song of Solomon. Erich Auerbach describes the Bible as a text "fraught with background" (qtd. in Alter, "The Old Testament" 22); the Song of Solomon is a text fraught with the background of the Bible. Here, I concentrate on Morrison's use of biblical names. The novel's epigraph~~~"The fathers may soar and the children may know their names"~~~signals the central role names will play in the novel. Over and over again, characters and places are named, renamed, or misnamed, and more often than not, the Bible is at the centre of this process. The title of the novel and the names of almost all the women and some of the men come from the Bible. Each one of these names evokes complex biblical characters, allusions, metaphors, and narrative cycles that resonate back and forth throughout the text, and each name signals a parallel with, reversal of, or contradiction with a given biblical allusion.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.028 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".