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Record W2736838382 · doi:10.5539/ach.v9n2p46

Evolution of Residential Building in Iran based on Organization of space

2017· article· en· W2736838382 on OpenAlexvenueno aff
Mazdak Irani, Peter Armstrong, Amir Rastegar

Bibliographic record

VenueAsian Culture and History · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture and Cultural Influences
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanismArchitectureImitationSpace (punctuation)Function (biology)Identity (music)Architectural engineeringProcess (computing)YardSociologyEconomic geographyCivil engineeringEconomyGeographyAestheticsEngineeringComputer sciencePsychologyArchaeologySocial psychologyEconomics

Abstract

fetched live from OpenAlex

Iranian architecture and urbanism have developed in a historical process based on the different needs of people. The evolution of traditional Iranian architecture and urbanism may be characterized by eight factors: introversion, spatial organization, function of different parts, lifestyle, construction method, communication between houses, climatic conditions, and relationship with nature. In the recent decades, however, Iranian architecture and urbanism have faced a blind imitation of foreign cultures. The majority of modern buildings do not reflect the national identity of Iranian people. This paper investigates the architectural and urban transformation in Iran based on the rearrangement of building spaces. In doing so, the paper explores the development process of major interior and exterior elements such as public entrances, private entrances, kitchens, rooms, yards and open spaces. As a conclusion, while traditional Iranian architecture attempts to preserve the national identity and meet the different needs of Iranian people, the modern architecture is a blind imitation of western cultures.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.217
Teacher spread0.200 · 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 designQualitative
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

Citations4
Published2017
Admission routes1
Has abstractyes

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