Establishment of housing transfer inspection items using SEM: Empirical study in Taiwan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Disputes during the housing transfer process often lead to dissatisfaction for homeowners. This study aims to address these issues by (1) proposing a comprehensive house inspection guideline with key items and criteria, and (2) evaluating how inspection services influence homebuyers’ purchase intentions and perceived value. Based on comprehensive literature review and expert input, eight major inspection categories and 43 criteria were identified. These formed the basis for a Structural Equation Modeling (SEM) framework and three hypotheses. A pilot survey with 50 participants confirmed strong reliability (Cronbach’s Alpha: 0.880–0.945). Of 500 distributed questionnaires, 206 valid responses were collected. SEM analysis showed that inspection services significantly enhance both purchase intentions and perceived value, with R² values exceeding 79% in most areas, except for environmental inspections. Building structure, water supply/drainage and water leakage are the most influential findings in shaping perceived value. These results highlight the importance of targeted inspection services in addressing homebuyer perceived value and improving the overall housing experience in Taiwan.
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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 | 0.001 | 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 it