An Open Lab? The Electronic Textual Cultures Lab in the Evolving Digital Humanities Landscape
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
As the scholarly landscape evolves into a more open plain, so do the shapes of institutions, labs, centres, and other places and spaces of research, including those of the digital humanities (DH). The continuing success of such research largely depends on a commitment to open access and open source philosophies that broaden opportunities for a more efficient, productive, and universal design and use of knowledge. The Electronic Textual Cultures Laboratory (ETCL; etcl.uvic.ca) is a collaborative centre for digital and open scholarly practices at the University of Victoria, Canada, that engages with these transformations in knowledge creation through its umbrella organization, the Canadian Social Knowledge Institute (C-SKI), that coordinates and supports open social scholarship activities across three major initiatives: the ETCL itself, the Digital Humanities Summer Institute (DHSI; dhsi.org), and the Implementing New Knowledge Environments (INKE; inke.ca) Partnership, including sub-projects associated with each. Open social scholarship is the practice of creating and disseminating public-facing scholarship through accessible means. Working through C-SKI, we seek ways to engage communities more widely with publicly funded humanities scholarship, such as through research creation and dissemination, mentorship, and skills training.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.047 | 0.013 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it