Bibliographic record
Abstract
Purpose The purpose of this paper is first, to assess the applicability of the ideal of mixed‐use nodal development to a small town and rural setting. Second, it aims to model the patterns of density of the built environment, distribution of amenities and associated variations in travel distances and to show how all three have changed over the last decade in Antigonish town and county (Nova Scotia, Canada). Design/methodology/approach The core of the paper is a quantitative analysis, using GIS software to measure the changes in the built environment described in the second purpose (above). Findings The trend in Antigonish has generally been away from nodal development and towards increased commercial sprawl and increased distances between residences and amenities. However, there are realistic opportunities for reversing this trend. Research limitations/implications The paper suggests improved measures of access to amenities (to include employment) and improved measures of walkability using GIS. Practical implications The findings of this paper are directly applicable to planning to improve the social amenities and environmental sustainability in a small town/rural context. Originality/value There is very little literature on the applicability of theories of nodal development in a small town/rural setting. This paper addresses that problem and brings innovative GIS techniques to bear on it.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".