The Lady’s Museum Project, a Digital Critical and Teaching Edition of Charlotte Lennox’s Lady’s Museum (1760-61), Completes Phase Two of its Three-Phase Development Schedule
Bibliographic record
Abstract
The Lady’s Museum (1760–61) was among the most important early periodicals largely written by one of the most important eighteenth-century authors, Charlotte Lennox, whose multigenre, proto-feminist writing is beginning to receive the critical and pedagogical attention it deserves. Yet no modern edition of the text has existed—until now. Launched in 2021, the Lady’s Museum Project is presenting the first critical edition of—and learning community around—Lennox’s Museum in three open-access formats to encourage the widest possible readership: a non-specialist digital, interactive edition of the text and LibriVox audiobook intended for public and undergraduate-student audiences, and a specialist digital edition intended for scholars’ use—and participation (forthcoming). 2023 brought the completion of the teaching edition, which has been used in a variety of institutions across the U.S. and Canada, from 1000-level undergraduate to 5000-level graduate courses, and in undergraduate- and graduate-level internships designed to prepare interns for careers in editing and publishing, with a focus on transcending traditional teaching, editing, publishing, and disciplinary hierarchies and conventions.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".