Projektmanagement und Digital Humanities : Zur klugen Gestaltung der Zusammenarbeit
Bibliographic record
Abstract
Die Rahmenbedingungen für Projekte in den Digital Humanities können herausfordernd sein: Zum einen ist die Innovationserwartung beteiligter Institutionen und Fördergeber ungebremst. Zum anderen bedürfen die Koordination interdisziplinärer, komplexer Großvorhaben sowie der Aufbau von Forschungsinfrastruktur und -services einer Professionalisierung des Projektmanagements. Die Beiträger*innen geben Einblicke in unterschiedliche Praktiken und versammeln Sichtweisen aus der Fachcommunity. Damit gehen sie den ersten Schritt, um das Tätigkeitsfeld in den deutschsprachigen Fachdiskurs zu holen - und zeigen durch theoriegeleitete Reflexionen methodologische Ansätze zu einer Weiterentwicklung des Wissenschaftsmanagements auf.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.012 | 0.013 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.128 | 0.074 |
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".