Bibliographic record
Abstract
The recent quantitative turn in literary studies has reminded us of the breadth and variety of the literary field of the past. In so doing, however, it has necessarily levelled out the felt distinctions between various texts, and so risks working against the very sort of literary history that its new vistas promise: one which does justice to the workings of form across time and space. In particular, the presumptive interchangeability of texts that is required to put them into a series susceptible to quantitative analysis ignores the massively different footprint left by commercially successful (and socially canonical) texts as we move beyond their moment of initial publication. Evelina, for example, may have been just another novel of 1778 when it first appeared, but it loomed far above all other productions of that year a decade later (or anywhere beyond the metropole). Such footprints, I argue, changed the significance of their texts' form, making it seem richer, thicker, more resonant or definitive—perhaps, for some, more stifling or oppressive—than that of their apparently similar but less successful counterparts.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".