Impacts of Agritourism on Social Capital during the COVID-19 pandemic in Rural Ontario
Bibliographic record
Abstract
The development of agritourism has been a successful method used to diversify income and provide more financial sustainability for small scale farms that was used during and prior to the COVID 19 pandemic. The purpose of this research is to examine the current state of agritourism in southwestern Ontario 2 years into the COVID-19 pandemic. The pandemic safety protocols, defined by the Ministry of Health and local public health units, called for social distancing protocols which meant social events could not be hosted inside. Hosting events outdoors became a mode for safe social gatherings. There have been many opportunities with the development of outdoor social spaces; the future of social gatherings is still very uncertain because we are still in the midst of the pandemic. The research aims to identify the linkages between social experiences with agritourism and the knowledge and appreciation for local agri-food systems throughout the pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".