Bibliographic record
Abstract
Title: Sous Rature in Vernacular Architecture: Comparative Analysis of TMII and Dakshinachitra Open Air Museum Vernacular architecture reflects cultural identity, local values, and the relationship between people and their environment. Ex-situ conservation, such as open-air cultural museums, has become one of the strategies for preserving local architectural traditions as expressions of regional identity. When vernacular architecture is exhibited, it often becomes a representation separate from its original context. This study aims to examine how ex-situ conservation may erase, preserve, or leave traces of the meaning of vernacular architecture, and to analyze how aspects of vernacularity can be maintained in conservation practices. The research adopts a qualitative approach through a comparative case study of two open-air cultural museums, Taman Mini Indonesia Indah (TMII) in Jakarta and Dakshinachitra in Chennai, India. The analysis is conducted through a literature review, visual observations, and critical inquiry, using the conceptual lens of sous rature within the Derridean poststructuralist framework. The findings reveal that both cases experience contextual loss due to relocation. Dakshinachitra, on the other hand, uses placemaking strategies to protect the technical, social, and cultural aspects of vernacular architecture. In contrast, TMII presents symbolic visual representations that are disconnected from their local context. These findings underscore the value of conserving traditional architecture not only in its physical form but also in preserving its meanings, narratives, and ecological relationships.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".