Transcribing “Le Pèlerinage de Damoiselle Sapience”: Scholarly Editing Covid19-Style
Bibliographic record
Abstract
This article describes a methodological experiment conducted during the 13th Annual (Virtual) Schoenberg Symposium on Manuscript Studies in the Digital Age, hosted by the University of Pennsylvania, November 18–20, 2020. The experiment consisted of a “relay style” event in which three teams transcribed, revised, and prepared for submission to this journal a full edition of the “Le Pèlerinage de Damoiselle Sapience” and other texts from UPenn Ms Codex 660, ff. 86r–95v within the three-day timespan of the conference. The project used methods typical of crowdsourcing and drew participants from all over the world and from all different stages of their careers. After one group completed its work, the results were passed into the hands of the next. The final result—in the form of a finished manuscript edition, ready for submission to Digital Medievalist—was presented on the last day of the conference. The main purpose of this experiment was to demonstrate how the work of the transcriber and editor might be structured as a short-term digital event that relied wholly on virtual interactions with both the source materials and among collaborators. This method also reveals the positive aspects of the many challenges posed by working simultaneously, remotely, and globally.
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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".