An analysis og the agritourism in Westerm Newfoundland: potentials & impediments.
Bibliographic record
Abstract
The Agriculture, Aquaculture and Fishery sector of Newfoundland and Labrador plays important role in terms of its contribution to the employment and gross domestic product despite the fact that the sector has recently been under enormous pressure from structural changes. Producers in Newfoundland and Labrador are facing a series of challenges, including high production costs arisen from increasing inputs prices, rules and regulations imposed by the federal and provincial governments, increased competition in output markets, and the turmoil of global economy. As a result, producers will have to find new ways that generate additional income to the on-farm revenues. Agritourism is one option that can potentially increase the incomes of small farms while preserving the viability of rural economies in the region. This paper aims to analyse the agritourism industry in Western Newfoundland by conducting a comprehensive field survey during spring and summer 2008. The recommendations made from the results of this study provide new visions for policy makers to understand better the industry, recognise the impediments, and make appropriate decisions at the local and provincial level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".