Bibliographic record
Abstract
In contemporary India, the museum remains a symbol of cultural prestige, yet according to national cultural surveys, fewer than 1% of Indians visit museums annually, a statistic that reflects not only structural and spatial exclusions, but also psychological barriers shaped by class, language, and institutional codes of conduct. These institutions are far from neutral: they embed expectations about how to see, move, and behave, privileging a didactic framework. In the absence of intimacy, dialogue, and belonging, the museum becomes a space visited, not inhabited. Rather than viewing space as a container for artifacts, this thesis reimagines space itself as an artifact that unfolds gradually, through movement, pause, and return. It challenges the limitations of institutional typologies through strategies of decentralization. How can museums be reimagined as porous spaces that invite dialogue and embed themselves within communities? Inspired by the conception of museums as “looking glasses” for wonder and emotion, this thesis is situated within a two-story vernacular bungalow in Bandra, Mumbai. Embedded in a neighborhood shaped by migration, artistic practices, and layered identities, the bungalow offers more than just a site—it offers a social network. Its transitional edges, fragmented volumes, and lived-in spatial structure resist institutional formality, allowing the museum to unfold not as a place of authority, but as a space of relation. By adapting the existing structure, this thesis explores design strategies centered on soft thresholds, blurred boundaries, and spatial porosity. It develops a spatial language that holds, frames, and reveals meaning through detail—composing relationships between rooms, courtyards, and passages. This language is built on gestures of joining, layering, concealing, and opening—subtle acts that shape the relationships between people, space, and cultural narratives.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".