Towards Language Sensitivity and Diversity in the Digital Humanities
Bibliographic record
Abstract
English Recent years have seen a growing focus on diversity in the digital humanities, and yet there has been rather less work on geolinguistic diversity, and the research which has been carried out often focuses on the structures of geographic representation in the field or has viewed ‘language’ as a technical or linguistic problem to solve. This article takes a different view, namely that we need to consider this diversity through multiple ‘frames’ of digitally-mediated language and culture, and that this is not just a question of epistemic justice or community manners, but that the digital humanities also need to address more actively challenges around global dynamics of digital multilingualism, transcultural exchange and geodiversity in its research agenda. This paper explores these questions through the prism of ‘language indifference’ in digital studies and, responding to Galina’s call for better data on the state of geolinguistic diversity in DH (2014), it articulates possible frameworks for addressing this diversity in a strategic, programmatic and research-led manner. We conclude by exploring the role of a greater multilingual focus in what Liu calls ‘the techne of diversity’ in digital humanities (2020), and contend that the digital humanities has much to gain, and much to offer, in engaging more fully with the languages-related cultural challenges of our era. RésuméCes dernières années l’accent a été mis de plus en plus sur la diversité dans les sciences humaines numériques, et pourtant il y a plutôt eu moins de travaux sur la diversité geo linguistique, et les recherches qui ont été menées portent souvent sur les structures de la représentation géographique sur le terrain, ou estiment le ‘langage’ comme un problème technique ou linguistique à résoudre. Cet article adopte un point différent, à savoir que nous devons considérer cette diversité à travers plusieurs ‘cadres’ de culture et de language à médiation numérique, cela n’étant pas uniquement une question de justice ou de savoir-faire communautaire, mais que, dans son programme de recherches, les sciences humaines numériques doivent également relever plus activement les défis à la dynamique mondiale du multilinguisme numérique, aux échanges transculturels et à la geo diversité. Ce document explore ces questions à travers le prisme de ‘l’indifférence linguistique’ dans les études numériques et, en réponse à l’appel de Galina pour de meilleures données sur l’état de la diversité geo linguistique dans DH (2014), il définit des systèmes possibles pour faire face à cette diversité de manière stratégique, programmatique et axée sur la recherche. Nous en concluons qu’en explorant le rôle d’une meilleure focalisation sur le multilinguisme dans les humanités numériques de ce que Liu appelle ‘la tech de la diversité’ (2020) et nous soutenons que les sciences humaines numériques ont beaucoup à gagner en s’engageant pleinement dans les défis culturels liés aux langues de notre époque.Mots-clés: Humanités numériques multilingues, Diversité linguistique et culturelle, Langues modernes numériques, Indifférence linguistique, Perturber le monolinguisme numérique
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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 | 0.023 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.011 | 0.078 |
| Scholarly communication | 0.027 | 0.031 |
| Open science | 0.002 | 0.034 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".