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Record W6924894175 · doi:10.17169/refubium-31546

Sprechen im Umbruch: Erzählen, erinnern, reagieren auf den Berliner Mauerfall

2021· article· de· W6924894175 on OpenAlexaboutno aff

Bibliographic record

VenueRefubium (Universitätsbibliothek der Freien Universität Berlin) · 2021
Typearticle
Languagede
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPragmaticsContext (archaeology)Foundation (evidence)Promotion (chess)Miller

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.439
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.010
Science and technology studies0.0040.001
Scholarly communication0.0000.006
Open science0.0030.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0270.018

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.

Opus teacher head0.050
GPT teacher head0.334
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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