Neither Computer Science, nor Information Studies, nor Humanities Enough: What Is the Status of a Digital Humanities Conference Paper?
Bibliographic record
Abstract
This paper explores the disciplinary and regional conventions that surround the status of conference papers throughout their lifecycle from submission/abstract, review, presentation, and in some cases, publication. Focusing on national and international Digital Humanities conferences, while also acknowledging disciplinary conferences that inform Digital Humanities, this paper blends close readings of conference calls for papers with analysis of conference practices to reckon with what constitutes a conference submission and its status in relationship to disciplinary conventions, peer review, and publication outcomes. Ultimately, we argue that the best practice for Digital Humanities conferences is to be clear on the review and publication process so that participants can gauge how to accurately reflect their contributions.Cet article explore les conventions disciplinaires et régionales qui entourent le statut d’articles présentés à des conférences durant leurs cycles de vie ; leur soumission/résumé, leur revue, leur présentation et, dans certains cas, leur publication. En se concentrant sur des conférences d’humanités numériques nationales et internationales et en reconnaissant des conférences disciplinaires incorporant les humanités numériques, cet article intègre des lectures attentives d’appels de propositions pour des conférences avec une analyse de pratiques de conférences afin de tenir compte de ce qui constitue une soumission de conférence et son statut par rapport à des conventions disciplinaires, à la critique des pairs et aux publications. Finalement, nous soutenons que les bonnes pratiques pour les conférences d’humanités numériques consistent en un processus de revue et publication clair qui permet à des participants de mieux comprendre comment représenter leurs contributions de façon précise.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.033 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".