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Record W3013938945

Memorialization and the Limits of Reconciliation: Transnational Memory Circuits of the Korean War

2019· article· en· W3013938945 on OpenAlexfundno aff
Kristen Sun

Bibliographic record

VenueeScholarship (California Digital Library) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsnot available
FundersYork UniversityHarvard UniversityNorthwestern UniversityEwha Womans UniversityTemple UniversityUniversity of MinnesotaSocial Science Research Council
KeywordsMemorializationTheme (computing)Spanish Civil WarHistoryIdeologyNarrativeChinaMedia studiesCultural memoryPoliticsLawGender studiesPolitical scienceSociologyLiteratureAnthropologyArt
DOInot available

Abstract

fetched live from OpenAlex

The Korean War, as a “hot war” within the Cold War period with participation by 21 member nations of the UN and the People’s Republic of China, and also an unresolved civil war between South Korea and North Korea, is characterized by still-present animosities, which play out in contemporary politics in the Asia-Pacific region, as well as for the U.S. Furthermore, memoryscapes of the Korean War continue to be shaped and reshaped in the present. My dissertation examines built spaces and cultural texts of Korean War memorialization, focusing specifically on films, museums, and memorials in South Korea and the U.S. in the “post-Cold War” conjuncture. It focuses specifically on the theme of reconciliation to ask, how do Korean War memorial texts and spaces attempt to reconcile an unfinished Cold War conflict in a post-Cold War world?I trace the theme of reconciliation in multiple ways – first, I utilize the common definition of reconciliation as an act of bringing issues to an agreement. For example, how do memorial texts and built spaces suture histories and memories into coherent or cohering narratives? Furthermore, I examine reconciliation as a specific affective theme in South Korean popular and national cultures, particularly through the imagined reunification between South Korea and North Korea, and/or separated family members stuck on opposite sides of the DMZ border as well as divided ideologically. Lastly, I examine reconciliation as a conceptual theme underlying memorialization of the Korean War in relation to Cold War memory and history – what is the relationship between memorialization and history, particularly as memorial and national texts attempt to make sense of Korean War history (as a technically unfinished war) with Cold War history (as a “finished” event)?Memorials and national/popular memory of the Korean War are thus necessarily changing or constantly being amended in flux with changing presidential administrations as well as in response to veterans or civic groups in both the U.S. and South Korea. In studying the memory of war, it is impossible to ignore the ways in which memory and memorial discourses travel across geographic space in reference to each other, whether intentional or not. Drawing from the rich genealogy of Asian American cultural critique, this dissertation argues that critical Asian American memorial studies as methodology to study memorialization can bring out transnational narratives and allows for the multiple subjectivities of museum/memorial visitors and film viewers to enable readings beyond existing Cold War frameworks and narratives in both South Korea and the U.S. Through conducing a transnational study of Korean War memory, this dissertation rethinks the Korean War as “forgotten war” or as the benchmark for showcasing South Korean developmentalism (“forgotten victory” discourse), but rather the nuances in differential layers of forgettings and rememberings that constitute Korean War memoryscapes in the “post-Cold War” period.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.016
Scholarly communication0.0130.017
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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