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Record W4367047319 · doi:10.1017/9781009233088.006

Staging a Scientific Debate

2023· book-chapter· en· W4367047319 on OpenAlexaff
Till Düppe

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsBureaucracySocialismMarxist philosophyCentralized governmentPoliticsDemocracyEconomic historyPeriod (music)Political scienceGermanPolitical economySociologyLawHistoryCommunismPhilosophyAesthetics

Abstract

fetched live from OpenAlex

Part II recounts the formative period of East German economists’ intellectual coming of age during the period of the so-called Thaw. The years after the Soviet break with Stalinism created hopes for a more democratic and decentralized socialism, hopes that were crushed by Ulbricht’s so-called revisionism campaign. This chapter focuses on the short career of Arne Benary (1929–1971), an economist related to Friedrich Behrens at the Central Economic Institute of the Academy of Sciences and a first chosen victim of Ulbricht’s campaign. The field of knowledge at stake was the master discipline of the political economy of socialism, a thus far unwritten chapter in the Marxist tradition. What is a more “true” and less “revised” application of Marx? The top-down Stalinist centralism or more bottom-up approach as ventured, for example, in Yugoslavia, Hungary, or Poland? This chapter shows how the Stasi, similar to the well-known show trials under Stalin, staged a show debate that, in spite of its forced character, allowed Ulbricht to both resist the reform of bureaucratic centralism and claim his policies to be a scientific undertaking.

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)0.014
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0080.023
Scholarly communication0.0140.016
Open science0.0010.006
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0140.004

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 head0.059
GPT teacher head0.239
Teacher spread0.181 · 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.

Study designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicEuropean history and politicsFrench-language works237,207