What’s Under the Big Tent?: A Study of ADHO Conference Abstracts
Bibliographic record
Abstract
This study identifies how the flagship Digital Humanities conference has evolved since 2004 and continues to evolve by analyzing the topical, regional, and authorial trends in its presentations. Additionally, we explore the extent to which Digital Humanists live up to the characterization of being diverse, collaborative, and global using the conference as a proxy. Given the increased popularization of “digital humanities” within the last decade, and especially recent successes in popular press and grant initiatives, this study tempers the sometimes utopic rhetoric that appears alongside mentions of the term. Cette étude a pour but de cerner comment la conférence phare sur les humanités numériques a évolué depuis 2004 et continue à évoluer, en analysant les tendances thématiques, régionales et d’auteur dans ses présentations. De plus, nous explorons dans quelle mesure les humanistes numériques sont à la hauteur de la caractérisation en matière de diversité, de collaboration et de mondialisation, en utilisant la conférence comme intermédiaire. Étant donné la vulgarisation croissante des « humanités numériques » au cours de la dernière décennie, et en particulier les récents succès dans la presse populaire et les initiatives de subvention, cette étude modère la rhétorique parfois utopique qui apparaît aux côtés des mentions du terme. Mots-clés: ADHO; authorship; disciplinarité
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 | 0.013 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.021 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".