Laying Tracks as the Train Approaches: Innovative Open Access Book Publishing at Heidelberg University from the Editors' Point of View
Bibliographic record
Abstract
In April 2016, Heidelberg University's newly founded open access publisher heiUP launched the first volume of the new book series Heidelberg Studies in Transculturality. This article reports on the challenges, accomplishments, and setbacks that informed the entire editorial production process, not only of the first volume but also of the series and the publishing enterprise overall. The authors offer insights on crucial issues that any new open access publishing endeavour at an institution might face, namely acquiring manuscripts, designing and building workflows, and collaborating with partners to build an outlet for hosting the finished product. This article also illustrates how the goal of providing a new digital reading experience through an innovative HTML format, in addition to print-on-demand and PDF versions of each manuscript, affected the progress of the entire project. Finally, we report on what it took to deliver results.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.154 | 0.146 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".