Regional District of Nanaimo Regional Growth Strategy Review Background Report: Land Inventory & Residential Capacity Analysis
Bibliographic record
Abstract
which was first adopted in 1997. The RGS was last updated and adopted in 2003 and began a review process in the fall of 2007. This report provides an update of the land inventory and residential capacity analysis for the RGS study area 1. This is the third update of the land inventory analysis and residential capacity analysis, with previous updates occurring in 1995 and 2001. The update provided in this report uses 2006 data from the BC Assessment Authority, the 2006 Census of Canada, and other data sources. It also presents the analysis using the current jurisdictional geographies, and includes the recently incorporated District of Lantzville and the modified boundary of Electoral Area C. In addition, the residential capacity analysis takes into account constraints and a practical capacity to provide a more realistic estimate of capacity, which was not done in the earlier studies. Also, the residential capacity assessment is presented according to three different structural types of dwellings: single-detached units, other ground-oriented units, and apartments, which allow a more detailed comparison of supply with demand. This study was conducted under current Official Community Plan (OCP) land use designations, zoning and other land use-related bylaws for the member municipalities and electoral areas.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 0.009 |
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".