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Record W4367664950 · doi:10.1162/thld_a_00774

The Architecture of Animation: <i>Sungnyemun's</i> Cultural Fire, Materiality, and <i>Han</i>

2023· article· en· W4367664950 on OpenAlexaboutno aff
Yeo-Jin Katerina Bong

Bibliographic record

VenueThresholds · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureMateriality (auditing)DemolitionObsolescenceHistory of architectureAnimationHistoryBachelorVernacular architectureCultural historyArt historySociologyVisual artsArtAestheticsArchaeologyEconomic history

Abstract

fetched live from OpenAlex

May 01 2023 The Architecture of Animation: Sungnyemun's Cultural Fire, Materiality, and Han Yeo-Jin Katerina Bong Yeo-Jin Katerina Bong Yeo-Jin Katerina Bong is a Ph. D. student at the Daniels Faculty of Architecture, Landscape and Design at the University of Toronto. Her research broadly focuses on early modern architecture of Italy, focusing on the treatment of structural defects, destruction, and demolition by architects of the period. She also examines the undergirding cultural history and early modern reception of failed or failing buildings and connects them to our own concerns about building destruction, functional obsolescence, and heritage preservation in the twenty-first century. Her secondary research concentrates on the material construction and preservation of East Asian architecture, particularly timber buildings from the Joseon dynasty. Katerina received a bachelor's from the University of Toronto and a master's from the University of Pennsylvania in art and architectural history. She also serves as the graduate chair of the Graduate Student Advisory Committee for the Society of Architectural Historians. Search for other works by this author on: This Site Google Scholar Author and Article Information Yeo-Jin Katerina Bong Yeo-Jin Katerina Bong is a Ph. D. student at the Daniels Faculty of Architecture, Landscape and Design at the University of Toronto. Her research broadly focuses on early modern architecture of Italy, focusing on the treatment of structural defects, destruction, and demolition by architects of the period. She also examines the undergirding cultural history and early modern reception of failed or failing buildings and connects them to our own concerns about building destruction, functional obsolescence, and heritage preservation in the twenty-first century. Her secondary research concentrates on the material construction and preservation of East Asian architecture, particularly timber buildings from the Joseon dynasty. Katerina received a bachelor's from the University of Toronto and a master's from the University of Pennsylvania in art and architectural history. She also serves as the graduate chair of the Graduate Student Advisory Committee for the Society of Architectural Historians. Online ISSN: 2572-7338 Print ISSN: 1091-711X © 2023 Yeo-Jin Katerina Bong2023Yeo-Jin Katerina Bong Thresholds (2023) (51): 150–161. https://doi.org/10.1162/thld_a_00774 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Yeo-Jin Katerina Bong; The Architecture of Animation: Sungnyemun's Cultural Fire, Materiality, and Han. Thresholds 2023; (51): 150–161. doi: https://doi.org/10.1162/thld_a_00774 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThresholds Search Advanced Search This content is only available as a PDF. © 2023 Yeo-Jin Katerina Bong2023Yeo-Jin Katerina Bong Article PDF first page preview Close Modal You do not currently have access to this content.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.081
GPT teacher head0.256
Teacher spread0.175 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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