Developing Agritourism in Nova Scotia: Issues and Challenges
Bibliographic record
Abstract
Agritourism or farm tourism is increasingly recognized as an important alternative farming activity that can contribute to agricultural sustainability through diversification of the economic base, provision of educational opportunities to tourists, and the engendering of greater community cohesion. Farm tourism activities can include farm markets, wineries, U-Picks, farming interpretive centers, farm-based accommodation and events, and agriculture-based festivals. Nova Scotia is well positioned to offer a competitive agritourism product given its rich farming heritage and increasing pressure on farmers to diversify, however, it is apparent that certain barriers exist to developing market-ready agritourism-related products. This paper reports on the findings of a research project, which sought to identify the issues and challenges of developing agritourism in Nova Scotia from the perspective of stakeholder groups. Through the use of interviews and a focus group using a modified Nominal Group Technique (NGT) process, stakeholders identified several issues that impact on the development of agritourism in Nova Scotia. These include issues related to marketing, product development, government support, education and training, and partnership and communication. As agritourism is a relatively new concept in Nova Scotia, this study represents exploratory research with the purpose of bringing to light potential issues and challenges that future agritourism development must address.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".