Bibliographic record
Abstract
The Edwardian period is often figured as a garden party broken up by the First World War. Looking back on the early twentieth century from the perspective of the twenty first, a different, strikingly contemporary picture emerges: amidst social and technological change, world capitals were haunted by the threat of instability and economic inequality, while the political left faced urgent questions about its continued relevance. Contrary to the image of the period as complacent on the brink of disaster, my dissertation asserts that the Edwardians were deeply invested in building a better future through both political reform and literary comedy. Both comedy and progressive reform look toward the future; in both cases, the Edwardians negotiated between convention and innovation to attempt to create a more equitable future. The dissertation ultimately illustrates the crucial role of the period in literary history and how its lessons may inform our own, which it much resembles. In order to do so, my readings of specifically Edwardian texts are situated in relation to larger historical narratives of both comedy as a genre and political reform. The first chapter reads George Meredith’s “Essay on Comedy” (1877) and The Egoist (1879) alongside Gladstonian Liberal reforms. Like those interventions, the “Essay” looks toward beneficial changes within existing traditions, while The Egoist puts them into practice. The second chapter analyzes George Bernard Shaw’s Major Barbara (1905; 1907) alongside Edwardian discussions of social welfare. Shaw’s fictional Perivale St Andrews, patterned on contemporary company towns, critiques the shortcomings of Edwardian New Liberalism’s approach to a better future. The third chapter situates E.M. Forster’s Howards End (1910) in relation to the cascading crises engendered by the 1909 “People’s Budget.” Like its political moment, Forster’s novel makes failure the precondition of ameliorative possibility, a vision Forster carried beyond the writing of fiction. The persistence of Forsterian concerns is further examined in the final chapter on Zadie Smith’s NW (2012). Foregrounding Smith’s use of Forsterian elements to critique both the limitations of Forster’s vision and the attenuated futurity of neoliberalism, this final chapter asserts the resonances of the Edwardian period with our contemporary moment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".