Sprechen im Umbruch: Erzählen, erinnern, reagieren auf den Berliner Mauerfall
Bibliographic record
Abstract
NORBERT DITTMAR ist seit 2008 emeritus der Freien Universität Berlin. Studium der Germanistik, Romanistik, Slawistik, Philosophie und Soziologie in Freiburg im Breisgau, Konstanz, Berlin (FU) und Aix-en-Provence. Promotion 1974. Wissenschaftlicher Mitarbeiter im DFG-Projekt Zweitspracherwerb ausländischer Arbeiter, Lehrveranstaltungen (Heidelberg 1974-1978), Visiting Professor in Toronto (Vorlesung und Übungen zum Zweitspracherwerb, Ende 1978-April 1979), Professor in Berlin seit dem Sommersemester 1979. Teilredaktion der Zeitschriften Linguistische Berichte und Linguistics. Herausgeber des Handbuchs der Soziolinguistik, Mitherausgeber der Reihe Pragmatics and Beyond. Mitglied der Beraterkommission bei der European Science Foundation (Straßburg) für das Zweitspracherwerbsprojekt (Vergleich von fünf europäischen Ländern). Zusammen mit der Soziolinguistin Christine Paul hat Norbert Dittmar das Buch Sprechen im Umbruch, Zeitzeugen erzählen und argumentieren rund um den Fall der Mauer im Wendekorpus (2019)1 herausgegeben. In Bezug auf diesen Band wurde Prof. Dr. Dittmar interviewt.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".