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Agritourism as a Solution to Rural Revitalization: The Case Study of North Durham Region

2020· article· en· W3040921230 on OpenAlexaffvenueabout
Sarah Parish

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGeographyRegional scienceSocioeconomicsEnvironmental planningSociology

Abstract

fetched live from OpenAlex

The agricultural industry has a prevalent, long-standing history as a successful cornerstone in Ontario. This historical prevalence stands true for the Regional Municipality of Durham’s three northern townships: Brock, Scugog, and Uxbridge. Agriculture and livestock are a driving force within the three township’s economies. However, throughout the last three decades, agricultural production in Ontario’s rural townships have been negatively impacted by vertical integration, globalization, and the intensification of land-based activities. This research examines the role of agritourism as a viable solution to revitalizing the agricultural sector in North Durham Region. This study utilized in-depth interviews with farm operators who have diversified their farming practices to understand these questions; the motivations of farmers to diversify their farms through agritourism, how agritourism assists farming businesses, and strategies farmers use to implement agritourism into their current farming practices. This research is imperative for farm operators in rural Ontario and policy makers to ensure farms are able to remain economically competitive against the pressures of urbanization and changing global markets.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.273
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes3
Has abstractyes

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