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Record W2898316735 · doi:10.1017/slr.2018.202

Globalized Socialism, Nationalized Time: Soviet Films, Albanian Subjects, and Chinese Audiences across the Sino-Soviet Split

2018· article· en· W2898316735 on OpenAlexfundno aff
Elidor Mëhilli

Bibliographic record

VenueSlavic Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicBalkans: History, Politics, Society
Canadian institutionsnot available
FundersYork UniversityGeorge Washington UniversityPrinceton UniversityCity University of New York
KeywordsSchismSocialismFriendshipCommunismBattleChinaAgency (philosophy)Political scienceState socialismHistoryEconomic historyPolitical economySociologyAncient historyLawPoliticsSocial science

Abstract

fetched live from OpenAlex

In the 1950s, films like Sergei Yutkevich's Velikii voin Albanii Skanderbeg symbolized Albanian-Soviet friendship, which was said to be undying. The Soviets brought their reels and their famous actors to this corner of the Mediterranean, and they also designed the country's first film agency, baptized “New Albania.” By the early 1960s, however, the friendship was dead. Albania's communist regime sided with Mao's China during the dramatic Sino-Soviet schism. From instruments of friendship, films turned into weapons in a global battle over the soul of socialism. Unexpectedly, Albanian war films assumed revolutionary meaning—far away from the Balkans—during China's Cultural Revolution. Recapturing these zigzags, this article shows how globalized socialism interacted with national imperatives. Bringing about exchange on a cross-continental scale, socialism encouraged constant mental mapping, and it also produced competing temporal frameworks. Going beyond nationalized histories of cinema, the article draws on archival sources from three countries, including previously classified Albanian materials.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.005
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.020
GPT teacher head0.374
Teacher spread0.354 · 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 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

Citations17
Published2018
Admission routes1
Has abstractyes

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Same venueSlavic ReviewSame topicBalkans: History, Politics, SocietyFrench-language works237,207