Bibliographic record
Abstract
This study estimates the effect of spatial heterogeneity and housing‐unit attributes on the value of apartment housing in a densely urban Chinese housing market. This paper contributes to the literature in two ways. First, high‐rise housing complexes present complications in that the vertical dimension is important in purchase decisions—yet the spatial econometric literature has focused exclusively on two dimensions. We introduce a three‐dimensional (3‐D) spatial weights matrix to capture the potential for “within project” correlation among housing units located on different floors within a project. Second, a significant proportion of the world's population lives in urban high‐rise buildings but the literature has, for the most part, completely ignored such markets. Test statistics support the use of a 3‐D weight matrix; our application of the hedonic methodology to a dense, vertical housing market shows that it can be used to value amenities located within or adjacent to housing complex amenities. In our empirical example, though, we observe little difference in marginal valuation of amenities under a 3‐D weight matrix relative to a standard 2‐D weight matrix.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".