Bibliographic record
Abstract
The paper proposes a methodology that combines theoretical and practical aspects from human-computer interaction (HCI) and genetic criticism to trace and analyse prototype evolution. A case study illustrates this type of enquiry by examining the iterations and the dynamics of change in the design and development of the Transviewer, an interface for digital editions. The initial assumption is that such an analysis can inform existing models in interface design and possibly provide new ground for discussion in humanistic HCI. For instance by fostering broader reflections on software production as a technological and cultural artefact and the gradual shaping of the principles and metaphors underlying the construction of a certain type of knowledge, argument, or interpretation through an interface. Cet article propose une méthodologie qui combine les aspects théoriques et pratiques de l’interaction homme-machine (IHM) et la critique génétique afin de repérer et analyser l’évolution de prototypes. Une étude de cas illustre ce type d’enquête en examinant les itérations et les dynamiques du changement dans la conception et le développement de Transviewer, une interface pour des éditions numériques. La supposition initiale est qu’une telle analyse peut offrir des renseignements sur les modèles existants de la conception d’interface et peut potentiellement fournir de nouvelles informations à la discussion autour de l’IHM humaniste. Par exemple, cela peut faciliter de meilleures réflexions plus élargies sur la production de logiciels comme artefact technologique et culturel, ainsi que sur la formation progressive des principes et métaphores qui sont à la base de la construction d’un certain type de connaissance, d’argument, ou d’interprétation à travers une interface.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".