Bibliographic record
Abstract
This study examines novels with graduate student protagonists, referred to as graduate student novels or grad novels, and argues that such novels should be considered distinct from others about university experiences. It builds on previous scholarship that distinguishes between novels about professors and about undergraduates as academic and campus novels, respectively. Through the consideration of several grad novels, three common elements are identified as characteristic of the subgenre: a grad student protagonist who is introduced at a moment of stasis in their research or academic progress; the intervention of fate which dramatically impacts the protagonist's story, and a conclusion that alludes to or explicitly depicts a kind of success in academia. The recognizable characteristics that illustrate the major differences, also provide helpful avenues toward examinations of the image of graduate scholarship produced by grad novels and different issues related to higher education. The initial stasis is examined as allegorical for the recently identified developmental stage of the quarter life and the quarter life crisis. The significance of fate and the protagonists' lack of agency is discussed alongside considerations of anti-intellectual sentiments. And the fictional academic success is read in comparison with academic quit lit written by scholars leaving academia. This dissertation considers the graduate novel as capable of being read both as an allegory and as representative of the actual experiences of scholars-in-training. It concludes with a contemplation of the potential alternative interpretations of readers inside and outside of academia.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".