Modeling Type Choice Outcomes of Housing Development Projects in the City of Hamilton, Canada
Bibliographic record
Abstract
This paper investigates the locational factors affecting the type of developed housing projects in the City of Hamilton, Canada in the period 1996 – 2001. The analysis relies on a micro-level land parcel geographic information system (GIS) dataset that was acquired from the City of Hamilton and TerraNet Incorporated. The parcel data were coupled with the Canadian census data and the CanMap Streetfiles data produced by Desktop Mapping Technology Incorporated (DMTI). Several variables were created and introduced in the specification of a number of Multinomial Logit (MNL) models. The models are specified and estimated to explain the housing-type choice behavior of land developers in the city. Four alternative type-choices facing developers are modeled: detached, semi-detached, row-link, and condominium housing. The specification of the four utilities includes locational factors depicting road infrastructure, residential amenities, and general site characteristics variables. The estimation results suggest that developers supply detached, row-link, and semi-detached houses at locations that exhibit suburban characteristics. However, semi-detached development is attracted to locations in suburban municipalities at sites that have more urbanized characteristics. In addition, the row-link housing type is attracted to suburban locations that enjoy very high levels of mobility and accessibility to amenities and road infrastructure. Finally, the condominium housing type is attracted to locations that exhibit the most urbanized features.
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 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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".