Virginia Woolf’s Common Readers in Paris
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article, we analyze historical, biographical, geolocational, and book distribution data from the *Shakespeare and Company Project* to understand Virginia Woolf’s readership in Paris in the 1920s and 1930s. The lending library cards from Sylvia Beach’s archive reveal the names of Woolf’s readers, and include important information about their reading habits and professional lives. The article uses a mixed-methods approach, combining historical and archival research on individual readers with visualizations of demographic, literary, and geographical data. Datasets from the *Shakespeare and Company Project* provide unique access to the networks of distribution, circulation, and readership that defined Woolf's literary presence in Paris. These networks, in turn, resonate with Woolf's own deep interest in her various readerships and publics.
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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 | 0.001 |
| 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 it