Bibliographic record
Abstract
The Data and Service Center for the Humanities ( DaSCH ) operates as a platform for humanities research data and ensures access to this data and promotes the networking of data with other databases (linked open data), to add value for further research and the interested public. As a competence center for digital methods and long-term use of digital data, it supports the hermeneutically oriented humanities in the use of state-of-the-art digital research methods. The DaSCH focuses on qualitative data and associated digital objects (images, sound, video, etc.) in the cultural heritage field. Long-term archiving or access is a major topic after the digital turn in the humanities, as many funding agencies such as the Swiss National Science Foundation and the European Commission are now requiring that a data management plan (D MP ) be in place to receive research funding. This new imperative raises many questions in the scientific community. This paper points out the contributions of the DaSCH for digital humanities researchers and the advantages of interoperability.
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 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 | 0.040 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.030 | 0.035 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".