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Record W2046128936 · doi:10.1080/14927713.2011.549194

Agrileisure: re-imagining the relationship between agriculture, leisure, and social change

2011· article· en· W2046128936 on OpenAlexvenueno aff
Ben Amsden, Jesse McEntee

Bibliographic record

VenueLeisure/Loisir · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationAgricultureSociologyHobbyTourismUrban agricultureGeographyPolitical science

Abstract

fetched live from OpenAlex

The role of farms and agricultural spaces is shifting and expanding. What was once primarily a space for work and production is now a de facto locus of rural and urban social change, illustrated by activities such as farm-based agritourism, home-based hobby farming, rural/urban farmers' markets and community-supported agriculture. In addition, agricultural spaces are seen by some as family-friendly places for recreation, education, small-scale production and personal growth. Much has been said to describe the importance of farming and local food as social movements, but in terms of leisure studies, current thinking leaves off after farm tourism. This suggests the need for a conceptual framework that addresses those who engage both the supply and demand sides of agriculture for the purposes of leisure and recreation. To this end, we present “Agrileisure” – an introductory framework with theoretical roots in leisure studies, ecology, sociology, psychology, social justice and geography.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.022
Scholarly communication0.0080.009
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.118
GPT teacher head0.247
Teacher spread0.129 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations42
Published2011
Admission routes1
Has abstractyes

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