Bibliographic record
Abstract
In today’s classrooms, teachers are often under great pressure — they not only have to prove themselves professionally but also as strong personalities. In teachers-training courses at universities, subject-related and didactic skills are often built up intensively, but there is a lack of support for personal and social skills, planning and management skills, and development skills. Extracurricular theater projects can compensate for this shortcoming. The paper presents effects of several years of theater work on teaching students studying German as a foreign language. Theoretically, the contribution is firstly underpinned by the approach of the Canadian sociologist Erving Goffman (2003) about self-portrayal in everyday life, in which he points out a similarity between acting and social contact [3]. Second, it is based on the understanding of the “performative competence” by Wolfgang Hallet (2010). Both concepts are transferred to the social contact between teachers and learners. Extracurricular theater projects can compensate for this shortcoming. The paper presents effects of several years of theater work on teaching students studying German as a foreign language. Theoretically, the contribution is firstly underpinned by the approach of the Canadian sociologist Erving Goffman (2003) about self-portrayal in everyday life, in which he points out a similarity between acting and social contact [3]. Second, it is based on the understanding of the “performative competence” by Wolfgang Hallet (2010). Both concepts are transferred to the social contact between teachers and learners.
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".