Supporting ethical and cultural competency development in cross-disciplinary information education in Germany
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper discusses development, teaching, and learning of a graduate level course on information ethics in a German academic setting. It provides an overview of student and course learning objectives, course design, approach to student engagement, assessment, and educational activities. The educational environment was cross-disciplinary between library and information science informed information ethics and computer science concepts and applications. Learning and teaching were contextualized to AI in medical domains, to support focus of educational environment. Ethical and cultural competencies were incorporated into course design to support application of information ethics in design choices, alongside European and United States guidelines on ethical AI. This paper also discusses experienced challenges to balancing disciplinary perspectives and European and North American pedagogical approaches. Specific, identifiable opportunities for future course expansion to support interdisciplinary, ethically, and culturally informed professional education are discussed.
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.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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 it