The Importance of Single Source Publishing in Scientific Publishing
Bibliographic record
Abstract
Academic publishing currently raises several issues, such as the production of multiple artifacts from a single source. The expression "single source publishing" refers to generating several formats from a single source. A single document can be used to produce various formats, without having to switch from one process to another, whether it is a PDF format for printing, an XML export for a digital platform, or a digital version in HTML format. This editorial challenge brings up both theoretical and technical questions, such as the legitimization of content, the evolution of publishing practices, and the creation of adequate tools. At the intersection of media studies, publishing studies, and literature, the concepts of hybridity (McLuhan, 1968), hybridization (Ludovico, 2012), or editorialization (Vitali-Rosati, 2016) allow us to question the principles of this editorial design.Actuellement, les publications académiques soulèvent plusieurs questions, telles que la production d'artefacts multiples à partir d'une source unique. L'expression "publication à source unique" fait référence à la production de plusieurs formats à partir d'une seule source. Un même document peut être utilisé pour produire différents formats, sans devoir passer d'un processus à l'autre, qu'il s'agisse d'un format PDF pour l'impression, d'un export XML pour une plateforme numérique, ou d'une version numérique au format HTML. Ce défi éditorial soulève des questions à la fois théoriques et techniques, telles que la légitimation des contenus, l'évolution des pratiques éditoriales et la création d'outils adéquats. Au croisement des études médiatiques, des études éditoriales et de la littérature, les concepts d'hybridité (McLuhan, 1968), d'hybridation (Ludovico, 2012) ou d'éditorialisation (Vitali-Rosati, 2016) permettent d'interroger les principes de cette conception éditoriale.
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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 | 0.054 | 0.180 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.068 | 0.035 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".