Transdisziplinäre Entwicklungsteams im ZZL-Netzwerk, Leuphana Universität Lüneburg
Bibliographic record
Abstract
In den letzten zwei Jahrzehnten wurden die intensiven Reformbestrebungen in Folge des sogenannten „PISA-Schocks“ durch eine breit und intensiv geführte Debatte über die grundlegenden Strukturen und Bedingungen in der Lehrkräftebildung begleitet. Kooperationen zwischen den Vertretern/-innen der drei Phasen Studium, Referendariat und Schuldienst stellen hierbei inzwischen altbekannte Forderungen mit dem Ziel einer besseren Verzahnung zwischen akademischer Ausbildung und berufspraktischem Handeln dar. Obwohl diese zunehmend im bildungswissenschaftlichen sowie pädagogisch-didaktischen Diskurs verhandelt werden und einschlägige Arbeiten zu angrenzenden Themen, wie bspw. Lehrkräftekooperationen (Fussangel 2008), interprofessionelle Zusammenarbeit (Dizinger/Fussangel/Böhm-Kasper 2011) und Bildungsnetzwerken (Kolleck et al. 2016) vorliegen, bestehen weiterhin zentrale Forschungs- und Entwicklungsbedarfe hinsichtlich der..
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
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".