Black Women in Ivory Towers: Race, Gender, and Class in British Campus Fiction
Bibliographic record
Abstract
How twentieth-century British women authors represent women academics in their fiction has been recently studied, but one key element has been missing: race. The twentieth century saw the systematic dismantling of the British Empire, increasing Commonwealth immigration, and rising racial tensions at home, as evidenced by the 2011 riots in north London. Yet given the close relationship between cultural and literary history, there seems to be no evidence of these dramatic cultural changes within the campus novel genre. Using Crenshaw's highly critical term intersectionality, this study focuses simultaneously on the lived experiences of Black women academics (through history, biography, and ethnographic study), as well as the literary interpretations of those lives. Focusing particularly on Judith Cutler's Dying Fall and Ahdaf Soueif's In the Eye of the Sun, this essay argues that the absence of and/or white-washed representations of Black Minority Ethnic (BME) women in British campus novels signifies how BME women's experiences are either rendered invisible or are subsumed under cultural norms of whiteness and middle-class identity.
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 | 0.001 | 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 | 0.015 | 0.011 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".