Jahrbuch des Migrationsrechts für die Bundesrepublik Deutschland 2024/25
Bibliographic record
Abstract
Das Jahrbuch des Migrationsrechts bietet den Rechtsanwender:innen auch für das Jahr 2024 einen schnellen, konzisen und zuverlässigen Überblick über die wichtigsten Entwicklungen im Aufenthaltsrecht, Flüchtlingsrecht, Staatsangehörigkeitsrecht und Flüchtlingssozialrecht in der Rechtsprechung (europäisch wie national), Gesetzgebung und Literatur. Die wissenschaftliche Abhandlung konzentriert sich auf die Vereinbarungen des Koalitionsvertrags zum Migrationsrecht für die 21. Legislaturperiode. Berichte zum Migrationsgeschehen aus dem Bundesamt für Migration und Flüchtlinge (BAMF) und des Deutschen Instituts für Menschenrechte (DIMR) runden den Band ab.Mit Beiträgen vonProf. Dr. Jürgen Bast | VRiBVerwG a.D. Prof. Dr. Uwe Berlit | Dr. Annika Fischer-Uebler | Johannes Graf | Klaus Hage | VPräsVG Dr. Michael Hoppe | Prof. Dr. Constanze Janda | RiLVerfG a.D. Prof. Dr. Winfried Kluth | Natalie Maurer | Edith Paintner | Inga Sessou | Camilla Schloss | Dr. Dana Schmalz | Dr. Friedrich Benjamin Schneider | Julian ThürySiehe vorab unter „Zusatzmaterial“ den Beitrag „Absprachen zum Migrationsrecht in der 21.Legislaturperiode: Annäherungen an den Koalitionsvertrag der schwarz-roten Koalition“ von Prof. Dr. Uwe Berlitzum kostenlosen Download.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.040 |
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".