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Record W1986859721 · doi:10.1177/1468797614563436

Organic farm volunteering as a decommodified tourist experience

2014· article· en· W1986859721 on OpenAlexaff
Maggie C. Miller, Heather Mair

Bibliographic record

VenueTourist Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTourismNexus (standard)Transformative learningAlternative tourismPublic relationsTourism geographySociologyConsciousnessSocial consciousnessMarketingBusinessPolitical sciencePsychologyPedagogyEngineeringLaw

Abstract

fetched live from OpenAlex

Volunteer tourism has been shown to foster cross-cultural understanding between participants and hosts. Providing opportunities to connect with like-minded participants, volunteer tourism experiences encourage consciousness-raising and future social and environmental actions. However, the laudable aims of volunteer tourism have been critiqued as their transformative capacities are overshadowed by industry attributes. Volunteering on organic farms, a movement associated with World Wide Opportunities on Organic Farms, mirrors components of volunteer tourism, although research on the nexus between the two is limited. Thus, through an exploration of volunteer experiences on organic farms in Argentina, this article advances our theoretical understanding of how volunteer tourism intersects with organic farm experiences and examines the possibilities and limitations of the “decommodification” paradigm in the volunteer tourism literature.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.005
Scholarly communication0.0020.001
Open science0.0000.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.326
Teacher spread0.294 · 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 designQualitative
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

Citations19
Published2014
Admission routes1
Has abstractyes

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