Bibliographic record
Abstract
The Digital Humanities 2010 (DH 2010) conference took place from July 7 through 10 at King's College London, where it was hosted by the Department of Digital Humanities (then Centre for Computing in the Humanities) and the Centre for e-Research, with the support of the School of Arts and Humanities, Information Services and Systems, and the Principal, Professor Rick Trainor. There were six satellite workshops, ten multi-speaker panels of ninety minutes each, eighty paper presentations, and twenty-three poster presentations. Over 300 scholars and students registered to participate in the conference. DH 2010 was a special occasion for many reasons. The Busa award was presented to Joseph Raben, emeritus professor of English as Queens College of the City University of New York (CUNY), inter alia in recognition of his founding the journal Computers and the Humanities in 1966 and the Association for Computers and the Humanities in 1978. Raben delivered a provocative lecture suggesting the computer will ultimately change not just humanities scholarship, but also the academic institutions it is part of. The Fortier prize, named after the late Canadian specialist on French literature and humanities computing, to be given to the best presentation by a young scholar at the conference, was awarded for the first time. Maceij Eder, Kraków, received the prize for his work on non-traditional authorship attribution. One of Eder's papers is included in this special issue. Masahiro Hori, Osamu Imahayashi, Tomoji Tabata, and Miyuki Nishio received the award for the best poster for ‘The Dickens Lexicon and its practical use for linguistic research’.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.363 | 0.210 |
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 source (direct Gemma or distilled Codex), 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".