カナダ自然公園の観光地での事例からみた日本における積極的な景観活用の研究への可能性について = The possibility of research on active utilization of landscapes in Japan from the perspective of cases at tourist sites of natural parks in Canada
Bibliographic record
Abstract
本報告では,豊富な自然資源を有しそれらを地域資源として観光や地域活性に活用している例が多くみられるカナダ西部の自然公園を訪問した際に確認された自然景観の積極的な活用事例の報告と,日本の観光等への導入の可能性について私見を交えて検討し,今後の研究課題の整理を行った。カナダの国立公園ではParks Canadaによる赤い椅子の設置が実施されており,椅子に座ることによって自然景観を楽しむ固定景を提供したり,自然公園における自然物を活用した一時的な観光地景観の人為的な改変,イルミネーションを施しての森林の夜観光への活用といった事例が見られた。これらを日本の観光地等に導入する場合には借景の活用や過去の固定景の活用,SNSによる撮影景観の活用などの事例を参考とすることが有効であると考えられ,カナダと日本を比較しながらのさらなる研究課題の設定が考えられた。
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".