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Record W4416368987 · doi:10.51255/2311-603x_2024_3_164

Holidays and memorable dates as an instrument of the historical policy of the Baltic states

2024· article· W4416368987 on OpenAlexaboutno aff
Kirill A. Zverev

Bibliographic record

VenueПетербургский исторический журнал · 2024
Typearticle
Language
FieldSocial Sciences
TopicEuropean Cultural and National Identity
Canadian institutionsnot available
Fundersnot available
KeywordsEstonianState (computer science)PoliticsIdeologyPopulationLatvianHistorical memoryQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

The article addresses the relationship between the holiday calendar of the Baltic republics and the local politics of memory. Following the attainment of independence, the Baltic states of Latvia, Lithuania and Estonia undertook a comprehensive revision of the Soviet holiday calendar, effectively eliminating all celebrations that were indirectly associated with the ideology of socialism. Concurrently, the Latvian, Lithuanian, and Estonian authorities employed the thesis of historical succession with regard to the interwar republics, restoring the 1930s calendar and incorporating several commemorative dates with an anti-Soviet and anti-Russian orientation. This act was designed to create a negative perception of the Sovietisation of the Baltic countries and to reinforce the image of victimhood for the states of the region during the Second World War. Nevertheless, there was no public consensus on the new calendar of commemorative dates (and consequently, on the state policy of memory itself). Conversely, the aforementioned theses were met with rejection by the majority of the Russian-speaking population of Latvia and Estonia, thereby exacerbating the ethno-linguistic divide within society, a process that was further compounded by historical factors.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0050.002
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 head0.027
GPT teacher head0.301
Teacher spread0.274 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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