Bibliographic record
Abstract
classification of "scholarship" are scholarly books, such as monographs and edited collections, but also editions and dissertations."Performances" covers stage productions at major theatres, audio recordings, and television and video productions, as well as musical scores.A recently added category, "Digital Projects, " lists items such as published PowerPoint presentations, interactive texts, and websites such as the MIT Digital Hamlet Project.The World Shakespeare Bibliography is, quite simply, an invaluable academic resource, offering a vast body of "professional" material, by which I mean work produced as part of an academic, artistic, or publishing industry.In recent years, the administrators have taken significant steps to ensure an easy user experience.The site is primarily designed as a search engine, with basic and advanced search options and a robust browsing menu.Once material has been found, it can be sorted by chronological, reverse chronological, alphabetical, and reverse alphabetical listings, or by document type.It is especially useful that the basic information can be expanded and collapsed when it appears in a list as the search results.The annotations of the text are as detailed as can be expected from a bibliography, with cross-reference tags that include relevant keywords, texts, and people; it is easy to save and export lists, and the e-mail 1.These reviews are published in collaboration with Early Modern Digital Review.They also appear in vol.2, no. 1 (2019) of EMDR (emdr.itercommunity.org).
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.017 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.186 | 0.236 |
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".