Relationship between Indoor Living Environment and Housing Prices: A Case Study of the Taojinjiayuan Residential Quarter in Guangzhou, China
Bibliographic record
Abstract
The indoor living environment of residential buildings is an important part of the habitat environment, affecting the living experience and well-being of the residents, which in turn influences the price of housing. However, few existing studies systematically concentrate on the integrated influence of the various elements of the indoor living environment on prices, and even fewer analyze the relationship between the indoor living environment and housing prices of different houses within the same residential quarter from a microperspective. Therefore, we use the Taojinjiayuan Residential Quarter, located in central Guangzhou City, China, as a case study area and analyze the extent and direction of the effect of the indoor living environment on housing prices. The study found that the quantitative evaluation results of the indoor living environment were reasonable. The integrated indoor living environment factors are closely related to housing prices. Orientation, view, and acoustic environment are significantly and positively related to housing prices, which have a different intensity of influence. These findings are beneficial to real estate developers, building designers, and residential users in quantitatively understanding the value of the indoor living environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".