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Record W4387952610 · doi:10.1080/14927713.2023.2271924

Regenerative leisure and tourism: a pathway for mindful futures

2023· article· en· W4387952610 on OpenAlexvenueno aff
Francesc Fusté‐Forné, Asif Hussain

Bibliographic record

VenueLeisure/Loisir · 2023
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsnot available
Fundersnot available
KeywordsTourismRegeneration (biology)RecreationFutures contractSustainabilitySociocultural evolutionIndigenousBusinessPolitical scienceEcologyBiology

Abstract

fetched live from OpenAlex

The emergence of regenerative tourism has gained worldwide momentum to raise awareness of the environmental and sociocultural impacts of recreational activities in host environments. The article examines leisure as human behaviour in its past, present and future perspectives to identify the current and future avenues of regeneration in leisure and tourist experiences. Although regenerative practices are much older than the COVID-19 pandemic, the current situation necessitates a focus on regenerative understanding that should be integrated into local systems both in the short and long term. Results suggest that to move beyond sustainability and the confines of capitalism, regeneration must be planned and developed in line with Indigenous values. Its effectiveness in reshaping leisure and tourism practices will depend on a collective commitment to finding innovative solutions that benefit the natural world and the diverse communities that interact with it because regeneration looks holistically at the relationship between humans and nature.

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)0.007
metaresearch head score (Gemma)0.004
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 score0.015
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0080.050
Scholarly communication0.0150.013
Open science0.0010.015
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0110.001

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 head0.032
GPT teacher head0.311
Teacher spread0.279 · 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

Citations15
Published2023
Admission routes1
Has abstractyes

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