Prototyping the Renaissance English Knowledgebase (REKn) and Professional Reading Environment (PReE), Past, Present, and Future Concerns: A Digital Humanities Project Narrative
Bibliographic record
Abstract
<span>The Renaissance English Knowledgebase (REKn) is an electronic knowledgebase consisting of primary and secondary materials (text, image, and audio) related to the Renaissance period. The limitations of existing tools to accurately search, navigate, and read large collections of data in many formats, coupled with the findings of our research into professional reading, led to the development of a Professional Reading Environment (PReE) to meet these needs. Both were conceived as necessary components of a prototype textual environment for an electronic scholarly edition of the Devonshire Manuscript. This article offers an overview of the development of both REKn and PReE at the Electronic Textual Cultures Laboratory (ETCL) at the University of Victoria, from proof of concept through to their current iteration, concluding with a discussion about their future adaptation, implementation, and integration with other projects and partnerships.</span>
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 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 | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".