NewRadial: Challenging scales and standards of humanities scholarship through new knowledge environment prototypes
Bibliographic record
Abstract
Even though large aggregations of humanities data are emerging through the efforts of significant federations, the larger the collection, the more difficult it is for large-scale standards to effectively account for and relate the complex variety of data objects and their characteristics. How can we simultaneously embrace this complexity with the help of the computer and achieve interoperability while still retaining the interpretative flexibility that is the heart of meaningful humanities work? Additionally, what scale is the optimal viewpoint through which we can do humanities-related work on such large data sets? At what point do we lose a humanist sensibility when working with big data, and how do we take advantage of computing technology to pluralize perspective, confront complexity, avoid reductiveness and preserve meaning as we interpret meaningful subsets of big data collections? NewRadial— an INKE prototype—addresses these questions by enabling users to connect and explore humanities databases across plural scales of engagement without imposing a universal metadata standard. Its web-based environment visually displays the objects of humanities databases in a manner that encourages browsing, searching, collecting, organizing, connecting and annotating, modelling a way to bring different standards and ontological perspectives together without negating their differences or requiring conformity to a reductive or limiting overall system. Même si de grands regroupements de données de sciences humaines voient le jour grâce aux efforts d'importantes fédérations, plus la collection est vaste, plus il est difficile pour les normes à grande échelle de tenir compte et de dépeindre efficacement la gamme complexe des objets de données et leurs caractéristiques. Comment cela peut-il être apprécié dans toute sa complexité avec l'aide de l'ordinateur et réaliser une interopérabilité tout en maintenant la souplesse interprétative qui est au cœur même du travail significatif des sciences humaines. De plus, quelle est l'ampleur du point de vue optimal par lequel le travail relié aux sciences humaines peut être accompli selon un tel vaste ensemble de données? À quel moment peut-on perdre la sensibilité humaniste en travaillant avec de larges données, et comment tirer parti de la technologie informatique pour pluraliser la perspective, confronter la complexité, éviter le caractère minimaliste et préserver le sens à mesure que l'on interprète les sous-ensembles significatifs des grandes collections de données? NewRadial— un prototype de INKE—répond à ces questions en permettant aux utilisateurs de relier et d'explorer les bases de données de sciences humaines à travers une pluralité d'échelles d'engagement sans imposer une norme universelle de métadonnées. Son environnement internet affiche visuellement les objets des bases de données de sciences humaines de façon à encourager la navigation, la recherche, la collecte, l'organisation, la connexion et l'annotation, en servant de modèle pour démontrer un moyen de rassembler différentes normes et perspectives ontologiques, sans remettre en question leurs différences ni exiger la conformité à un système global réducteur ou contraignant.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".