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Record W4412969879 · doi:10.1016/j.jort.2025.100925

Does intensity of nature-based recreation drive environmental stewardship?

2025· article· en· W4412969879 on OpenAlexaffabout
Kolsoum Heidari, François Gravelle

Bibliographic record

VenueJournal of Outdoor Recreation and Tourism · 2025
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRecreationEnvironmental stewardshipStewardship (theology)Environmental resource managementPsychologyEnvironmental planningBusinessEnvironmental sciencePolitical science

Abstract

fetched live from OpenAlex

While nature-based recreation is widely recognized for its well-being benefits, its role in fostering long-term environmental stewardship remains underexplored. This study bridges this gap by applying the Serious Leisure Perspective a framework that describes sustained, skill-intensive, and identity-building leisure participation, to examine how sustained engagement in outdoor activities cultivates ecological responsibility among recreationists in Gatineau Park, Canada. Using SmartPLS structural modeling, we analyzed survey data from 248 outdoor recreationists, assessing relationships between serious leisure (measured via the Serious Leisure Inventory and Measure) and environmental concern (using the New Ecological Paradigm Scale). Serious leisure significantly predicted environmental concern (R 2 = 0.563), with younger, educated participants showing heightened awareness. Subdimensions of environmental concern—anti-anthropocentrism (β = 0.329), balance of nature (β = 0.771), and ecological crisis (β = 0.766)—were strongly influenced by serious leisure engagement. Findings advance outdoor recreation research by demonstrating how serious leisure fosters place attachment and stewardship. We propose actionable strategies for park managers to design programs (e.g., skill-based workshops, citizen science) that leverage leisure engagement for sustainability outcomes. This study also can be used by park managers, environmental educators, and recreation planners looking for evidence-based strategies to encourage sustainable behaviors through leisure engagement.

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)0.001
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 score0.096
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.282
Teacher spread0.275 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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