"Though much is taken, much abides": Recovering antiquity through innovative digital methodologies: Introduction to the special issue
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
Classicists have long been at the forefront of the Digital Humanities. As is also true in mediaeval studies, this engagement with technology is due primarily to the complexity of the primary sources under consideration and patchy and often fragmentary state of these same artefacts.The papers in this collaborative issue of Digital Medievalist continue this tradition of cutting edge technological and disciplinary work. Drawing from papers presented at the inaugural Digital Classicist Work-in-Progress seminar series in London in the Summer of 2006 and adding other specially commissioned papers, this issue provides an in-depth view of current research in many of the most important areas in the Digital Classics: text markup and electronic publication; geotagging and network analysis; semantic web/social networking technologies; visualization and relational database tools. While the papers are all written with a disciplinary focus on the Classics, the research they discuss is of obvious interest to mediaevalists, and those working in the Digital Humanities more generally.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it