“Just One Thing More”: <i>Absalom, Absalom!</i> and the Creditor-Debtor Relationship
Bibliographic record
Abstract
To what extent, if any, can art provide us with a way of thinking outside of the creditor-debtor relationship? This article looks to William Faulkner's Absalom, Absalom! (1936) for an answer. I demonstrate, through a reading of the novel's anonymous lawyer, the extent to which the economic logic of the ledger (as a figure for the creditor-debtor relationship) penetrates the novel and its logic of storytelling. The article then goes on to examine, via an analysis of the novel's ending, two “remainders”—two elements that cannot be integrated into this economic logic. Finally, I draw on Judith Butler's work to suggest that Absalom, Absalom! does gesture toward a form of relationality outside of the economic terms of debit and credit, seen in Miss Coldfield's initial framing of her tale and in Butler's idea of “dependency.”
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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 | 0.001 | 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 | 0.005 | 0.025 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".