Architectural Concepts of Religious Buildings: Comparing Le Corbusier’s Notre Dame and Meier’s Jubilee Church
Bibliographic record
Abstract
Using architectural technology in religious building design can enhance the spiritual senses.However, it can distract us from prayer.This study aims to explain the role of technological tools in translating architectural concepts related to religious buildings, compared with the use of conventional techniques.Meanwhile, this study identifies certain principles that can help architects design religious buildings.The methodology involves a comparison between -Notre Dame church in France, designed by Le Corbusier in 1950-and Jubilee Church in Rome, designed by Richard Meier and built in 2003.The two churches are related to each other.Meier architecture has been recognized as a late modernism owing to the influence of Le Corbusier's visual approach.However, there are certain differences between them.The results demonstrate the role of technology in contributing towards making it easy to reflect spiritual concept.Furthermore, the study reveals how an architect can express spiritual concepts, even when there is no technological assistance, by utilising lighting, colour, space, form, and site forces.This study emphasizes that the prudent utilization of technological techniques can make it easier to produce a comfortable religious space.By contrast, the use of only traditional materials requires huge efforts and a long time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".