Extending the Middlebrow: Italian Fiction in the Early Twentieth Century
Bibliographic record
Abstract
The aim of this essay is to determine whether the concept of the middlebrow can also be translated to cultural and historical contexts other than the Anglo-American one in which it first originated. More particularly, we seek to investigate whether the term can usefully be applied to the Italian literary scene of the first part of the twentieth century. After a short introduction of the different historical and critical uses of the term in Britain and the U.S., we turn to Italy of the early twentieth century for a description of the numerous new developments in writing, publishing and marketing literature. Subsequently, we assess the different ways in which these changes have been analysed and conceptualised in Italian literary criticism, so as to point out the lacunae in this scholarship precisely with regard to writing that falls in between the categories of popular and high literature. By means of one more detailed case study, i.e. the work of the once popular and now forgotten writer Pitigrilli, we argue that his novels share many of the characteristics of the literature labelled as middlebrow in an Anglo-American context. The introduction of this term in Italian criticism, we argue, would undoubtedly lead to a more accurate assessment of his work – and that of other writers like him - within Italian literary history.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".