An examination of the land inventories of major private sector residential developers in Metropolitan Vancouver
Bibliographic record
Abstract
The focus of this study is on the role of the major residential developers in the Vancouver region in terms of the raw land inventories presently held and the difficulties encountered in adding to these land inventories to replenish land supply. The objective is to determine whether the major private sector developers can provide substantial relief from the present dwelling unit supply/demand imbalance. Information on the land holdings of twelve major developers was collected through the use of a questionnaire. Information as to the relative sizes of urban areas, sewer areas, sewer catchment areas, development areas, and the parcels within the development areas, was collated from planning reports, maps, and tabulation. Analysis of the data reveals that private sector developers do not have extensive land inventories in the Vancouver region. Further analysis points out that the inventories are in most cases, held for immediate development. Evidence shows that splintered land ownership patterns and small parcel sizes are instrumental in reducing raw land inventory sizes. Furthermore, evidence shows the combination of small parcel sizes, assembly difficulties and the direction of development toward specific development areas by municipalities sharply reduces the potential numbers of residential dwelling units.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".