„Same same, but different“ - Körperlichkeit und Moderation im virtuellen Raum
Bibliographic record
Abstract
Interaktives interkulturelles Lernen ist auch im virtuellen Kontext möglich. Praxis und Evaluation an der Universität Göttingen zeigen, dass Videokonferenzen Potential dazu haben. Gleichzeitig ergeben sich Herausforderungen, die durch den virtuellen Raum, Sichtbarkeit und persönliche Trennung begründet sind. Diese Herausforderungen sind verknüpft mit dem Thema Körperlichkeit und dem Fehlen von physischer Präsenz. Zur Sicherstellung einer hohen Interaktionsqualität fordert dies von der Moderation neben einem proaktiven Umgang einen bewussten Fokus auf Initiieren und Erhalt von persönlichen Beziehungen innerhalb der Gruppe von Lernenden. Darüber hinaus eröffnet die virtuelle Begegnung neue Möglichkeiten für erfahrungsbezogenes Lernen, indem der virtuelle Kontext als gemeinsamer interkultureller Kontext verstanden und zum Lerngegenstand gemacht wird.
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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 | 0.023 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".