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Record W3004633777 · doi:10.52086/001c.25420

‘The unacceptability of the erasures’: John Hejduk’s texts for the ‘Berlin Masque’

2019· article· en· W3004633777 on OpenAlexaff
Angeliki Sioli

Bibliographic record

VenueTEXT · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature and Cultural Memory
Canadian institutionsMcGill University
Fundersnot available
KeywordsAppropriationNarrativePropositionAestheticsUnpackingPower (physics)ArchitectureSpace (punctuation)Visual artsHistory of architectureCityscapeSociologyHistoryLiteratureArtEpistemologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Engaging Hejduk’s compelling project, ‘Berlin Masque’ (1981), this paper looks into writing’s power to develop unforeseen possibilities of architectural program. In his ‘Berlin Masque’ proposal, unlike his earlier ‘Masques’, Hejduk clearly prioritizes his prose – not his small accompanying sketches – as the place where the architectural proposition is primarily portrayed. Unpacking these texts in detail will indicate how language represents spatial elements and allow one to imagine moments of spatial appropriation, thus creating original architectural images of cultural significance. Furthermore, the paper demonstrates how Hejduk’s texts and new programmatic possibilities aspire to reconcile Berlin with the trauma of the Second World War. His proposal intends to remind the city’s inhabitants that history is not something that is limited to the past, but a development that involves new, everyday happenings and their interaction with memory. Expanding on the rituals of inhabitation for each suggested structure, as narrated in the texts, the paper outlines how the new stories proposed by the architect acknowledge the city’s existing narratives while creating the necessary space for new ones to appear. The conclusion extracts the significance and uniqueness of the ‘Berlin Masque’ as an architectural project, as well as the significance of language for Hejduk as an architect. It discusses briefly the noted interest in ar

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 categoriesInsufficient 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: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.220
Teacher spread0.203 · 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
Published2019
Admission routes1
Has abstractyes

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