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
This paper discusses approaches to digital editing, focusing on two projects, ReScript and Early English Laws (http://www.earlyenglishlaws.ac.uk). It also touches on some of the other tools available to editors, for example those offered as part of TextGrid. ReScript, a project of the Institute of Historical Research, aims to develop a prototype editing facility, which will support collaboration within established editorial teams as well as a crowdsourced approach to producing editions. It is currently being trialled with texts at a range of stages of production, from ‘completed’ 19th-century editions which will benefit from correction and annotation to completely new works. Early English Laws aims to publish online new editions and translations of all English legal codes, edicts and treatises produced up to and including Magna Carta in 1215. A bespoke editing facility has been developed by the Department of Digital Humanities at King’s College London which, like ReScript, will support collaborative editing, as well as export to print where appropriate. The latter project is particularly complex as it has to accommodate a variety of languages and editorial approaches (scholars working on early English texts, for example, have very different requirements from those working with Latin documents). The tools developed by both of these projects will be made available in due course for use and adaptation by and for other projects. The paper was given at the 'Envisioning REED in the digital age' workshop organised by the Records of Early English Drama project, University of Toronto, 4-5 April 2011.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.021 |
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