Facades of Historic Shop-Cum-Houses in Colonial Cantonment Towns in Bengal Presidency, India
Bibliographic record
Abstract
The historic quarters are an integral part of the urban fabric of a city and grant identity and character to it.These are the containers of both tangible and intangible cultural heritage.The market places of Colonial Cantonment towns in Indian sub-continent are one such type of settlement which are the display houses of architecture, art, social interactions, community participations and life style habits of the occupants at the time of their establishment.These historic urban landscapes are hubs of trade and commercial activities and showcase their transformation over the years.One of the unique typologies of structures which evolved with Colonization were the shop-cum-houses.This paper focuses on the shop-cum-houses as built heritage within the market places of Colonial Cantonment towns in the Bengal Presidency of India.This research paper studies the architectural elements and features on the facades of these structures within the Sadar Bazaar areas and analysis the evolution of the architectural style over the decades.The analysis is done through the survey of level II and III during which physical features were documented.The study reveals the impact of global architecture on the local craftsmanship and styles along with some characteristic features that were found persistent throughout granting identity to these historic landscapes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".