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Record W4311681039 · doi:10.22215/etd/2022-15304

Flowers for Stalin; Online Memory of a Dictator

2022· dissertation· en· W4311681039 on OpenAlexafffund
L. Glasser

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDictatorGeorgianNarrativeHEROSoviet unionPoliticsPolitical scienceMedia studiesEconomic historySociologyHistoryLawArtLiterature

Abstract

fetched live from OpenAlex

While Western society views Josef Stalin as a tyrant, in many post-Soviet countries, that is not the case. Russia and Georgia, the center of the former Soviet Union and Stalin's home country, respectively, are notable examples. This work will determine the roles of citizens and social media sites in interpreting Stalin's legacy and serve as an initial piece of research into the intersection of memory politics, social media, and post-Soviet states. I compare social media posts with each country's official narrative toward Stalin and determine that Russian and Georgian governments approach him differently, with Russia presenting him positively, and Georgia not having a cohesive official narrative. Findings were that both countries support the War Hero narrative, Georgians are proud of being from Stalin's home country, and youth are becoming indifferent towards him. This work will help outline the extent to which the Soviet era still influences the modern day. This paper could not have been written without the help and support of so many people. I am very thankful to my supervisor, Dr. Jeff Sahadeo, who had endless patience for my numerous rounds of edits and who was always willing to sit down

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.534
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0240.000

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 head0.034
GPT teacher head0.362
Teacher spread0.328 · 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 teacher head, not a consensus.

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
Published2022
Admission routes2
Has abstractyes

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