Bibliographic record
Abstract
Erich Auerbach's Mimesis is among the most admired works of literary criticism of the last hundred years. Amidst the horrors of the Second World War, Auerbach's prodigious learning managed – almost miraculously – to give voice to a delicate, subtle optimism. Focusing on Auerbach's account of Renaissance literature, Christopher Warley rediscovers the powerful beauty of Mimesis and shows its vitality for contemporary literary criticism. Analysing Auerbach's account of Renaissance love lyric alongside Woolf's To the Lighthouse, fifteenth-century Burgundian writing alongside Ferrante, and Shakespeare alongside Michelet, Ruskin and Burckhardt, Auerbach's Renaissance traces an aesthetic that celebrates the diversity of human life. Simultaneously it locates in Auerbach's reading of Renaissance writing a challenge to the pessimism of today, the sense that we live in an endless present where the future looms only as a threat. Auerbach's scholarship, the art he learns from Dante, Rabelais, Montaigne, and Shakespeare, is a Renaissance offering democratic possibility.
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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".