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Record W1545807897 · doi:10.1080/00905992.2015.1053388

Residual history: memory and activism in modern Poland

2015· article· en· W1545807897 on OpenAlexaff
Shona Allison

Bibliographic record

VenueNationalities Papers · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolish Historical and Cultural Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCollective memoryPoliticsUkrainianRelocationPolitics of memoryNewspaperConvictionPhenomenonPolitical scienceEthnic CleansingEthnic groupSociologyPolitical economyMedia studiesLawCriminologyHistoryEpistemologyComputer science

Abstract

fetched live from OpenAlex

This article examines the divide between national and local collective memory in Poland and investigates the role of “memory activists” in mediating and exploiting this divide. It narrows its focus to the ethnic cleansing of Poles by the Ukrainian Insurgent Army (UPA) from 1943 to 1944 and the forced relocation of Ukrainians in Poland, Operation Vistula, in 1947. It surveys local and national newspapers to understand competing interpretations and analyzes what incidents (e.g. protests, disputes, commemorations, reenactments, etc.) related to these events take place in local communities. It highlights the many actors, “memory activists,” and associations involved in pushing specific, often ahistorical, interpretations of these events – motivated by political gain, careerism, or personal conviction. It uses the theoretical works of Maurice Halbwachs and Karl Mannheim to effectively distinguish between local and national phenomenon and to elucidate the various nuances of collective memory.

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)0.002
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 score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.009
Scholarly communication0.0040.004
Open science0.0000.004
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 head0.082
GPT teacher head0.291
Teacher spread0.208 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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