Caldwell's Sexual Transgressions: An Examination of Race, Gender, and Sexuality in <em>God's Little Acre</em>
Bibliographic record
Abstract
While the last few decades has seen growing critical interest in Erskine Caldwell’s God’s Little Acre, much of that attention is focused on the novel’s stylistic attributes or its critiques of class and economics. In his essay “An Extravagance of Laughter” Ralph Ellison recounts his disruptive laughter at a performance of the stage adaptation of Tobacco Road, which was brought on by his realization that Caldwell had written common racist tropes of black sexuality onto white bodies. Given that God’s Little Acre was published when nation was so keenly attuned to the Scottsboro trials, one must ask if this novel also uses white bodies to expose racial assumptions about black sexuality. Darling Jill, a sexually aggressive white woman, and Dave the albino, a black man with white skin and a problematically submissive sexuality, are especially suited to examining the novel’s transgressive cross-scripting of sexuality. This paper examines the gendered stereotypes of black sexuality prevailing during the first quarter of the twentieth century; the contributions of the Scottsboro trials to the raced and gendered national discourse of sexuality; and a close reading of the sexual relationship of Dave the albino and Darling Jill to uncover how race, gender, and sexuality converge in ways that call to question deeply-rooted assumptions about black sexuality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".