The changing cultural differences between Japanese and Canadian inner ruralurban fringe residential landscapes
Bibliographic record
Abstract
There are a variety of residential combinations on the edge of cities owing in part to non-farm residences being mixed in with rural landscapes, including those of farm residences. In Canada, where there is a strong cultural connection with Europe, the large non-farm estate has been a characteristic type of housing in the rural-urban fringe. In Japan, on the other hand, large lot estate homes are absent. Instead, high density tract housing is usually found on the edge of cities along with randomly dispersed apartment buildings and non-farm houses among farmland. The purpose of this paper is to examine selected cultural differences between the Japanese and Canadian rural-urban fringe with a focus on residential landscapes, through a review of the literature, which is supplemented with landscape observations. The results are that in Japan rural landscapes on the edge of cities are increasingly being valued for their recreational, i.e., gardening, and natural qualities, and this can be related to a changing rural idyll, which has been based on agrarianism. In Canada we see the estate home – even close to the city -- due to an enduring rural idyll that originated in the European countryside, combined with larger lots, and a desire to preserve natural landscapes. The principal conclusion is that the rural idylls of Japan and Canada differ, and these differences are expressed in the inner rural-urban fringe landscape. However, the Japanese rural idyll appears to be merging with the Canadian rural idyll in terms of a desire to preserve nature in the inner rural-urban fringe.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".