What Violently Elects Us: Filiation, Ethics, and War in the Contemporary British Novel
Bibliographic record
Abstract
This dissertation examines the trope of filiation in novels by three contemporary British writers: John Banville, Ian McEwan, and Kazuo Ishiguro. \nThe trope of filiation and the related theme of inheritance has long been central to the concerns of the British novel, but it took on a new significance in the twentieth century, as the novel responded both thematically and formally to the aftermath of the two world wars. This study demonstrates the ways in which Banville, McEwan, and Ishiguro each situate their work in relation to this legacy, by means of an analogy between the inheritance structures figured within their novels and the inheritance performed by their engagement with the genre itself. \nThis study relies on an instructive analogy to similar treatments of the larger problem of cultural filiation by the theorists Emmanuel Levinas and Jacques Derrida. Levinas exposes in his work the ethical and political problems of modernist temporality by critiquing modernity’s rejection of filiation, a rejection modeled also in the lost children, and barren and celibate men and women of modernist novels. Derrida meanwhile provides a way forward with his representation and performance of inheritance as a critical and transformative act, which is characterised on one hand by an ethical injunction, and on the other, by a filtering or a differentiation which changes the tradition even as it reaffirms it.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.029 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".