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Germans 25 years after reunification — How much do they know about the German Democratic Republic and what is their value judgment of the socialist regime?

2015· article· en· W786282548 on OpenAlexaff
Daniel Stockemer, Greg Elder

Bibliographic record

VenueCommunist and Post-Communist Studies · 2015
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsGermanDemocracyValue (mathematics)CommunismEveryday lifePolitical scienceEastern BlocCommunist stateSociologyLawHistoryPolitics

Abstract

fetched live from OpenAlex

In this article, we evaluate German residents’ level of knowledge and their value judgment, that is, positive or negative, of the German Democratic Republic (GDR). Based on a simple random internet survey that asked 100 citizens from the East and 100 citizens from the West to describe life in the former GDR in at least 200 characters, we have found some nuanced results with regard to our two themes: First, our results indicate that the average German citizen has some decent knowledge of the Alltag or everyday life in the former East, with older individuals having significantly more knowledge than younger individuals. Second, we discover a clear pattern pertaining to peoples’ value judgment of life in communist Germany. Citizens born in the East have more positive memories of their Alltag in the GDR than citizens in the West who have not experienced life behind the Wall.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.333
Teacher spread0.275 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2015
Admission routes1
Has abstractyes

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