Digital Humanities Forum 2015. Afternoon session
Bibliographic record
Abstract
1:15 - 2:00 Panel Session: Up in Arms: The Collision of Intellectual Property and Collaborative Practices, Rachel Mann (University of South Carolina); The More the Merrier: Tapping into the Power of Librarians to Collaborate on Undergraduate Digital Humanities Assignments, Stewart Varner (University of North Carolina); Overlapping Hierarchies: Academic Libraries and Digital Humanities, Andrew Rouner (Washington University in St. Louis); 2:00 - 2:30 Performing archives: sensitive data, social justice, and the performative frame, Jacqueline Wernimont (Arizona State University); 2:30 - 3:00 The computer-assisted identification of meter and rhyme: How Russian is not English, David Birnbaum (University of Pittsburgh); 3:00 - 3:15 — Break —; 3:15 - 4:15 , Panel Session; Digital Cuba: Problems and Possibilities, Jonathan Dettman (University of Nebraska-Kearney); Critical Making, Platform Politics and Open Source in the Study of Digital Artworks, Andy Stuhl (Massachusetts Institute of Technology); Decolonizing Digital Humanities: Africa in Perspective, Titilola Babalola Aiyegbusi (University of Lethbridge ); eLaboraHd: Project of Digital Experimentation, Adriana Álvarez and Miriam Peña (National University Autonomous of Mexico (UNAM)); 4:15 - 5:15 Closing Keynote: “Networking Peripheries: Technological Futures, Digital Memory and the Myth of Digital Universalism”, Anita Say Chan, Assistant Research Professor of Communications, University of Illinois
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.011 |
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; both teacher heads agree on what is shown here.
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".