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Record W4380738891 · doi:10.5502/ijw.v13i2.2841

Cross-cultural validity of the Nature Relatedness Scale (NR-6) and links with wellbeing

2023· article· en· W4380738891 on OpenAlexaffabout
Zsuzsanna Kövi, Hyejeong Kim, Shanmukh V. Kamble, Veronika Mészáros, Danielle Lachance, Elizabeth K. Nisbet

Bibliographic record

VenueInternational Journal of Wellbeing · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsTrent University
Fundersnot available
KeywordsGratitudePsychologySocial psychologyScale (ratio)SpiritualitySocial connectednessWell-beingEudaimoniaCross-culturalMental healthSociologyGeographyAnthropology

Abstract

fetched live from OpenAlex

Nature relatedness refers to individual differences in subjective connectedness with the natural environment. We aimed to cross-culturally validate the Nature Relatedness scale and examine links between nature relatedness and wellbeing. We also tested whether spirituality or self-transcendent emotions such as gratitude mediate the relationship between nature relatedness and wellbeing. University student participants (N = 798) from four countries (Hungary, India, South Korea, and Canada) completed the short-form Nature Relatedness scale (NR-6; Nisbet & Zelenski, 2013), the Inclusion of Nature in Self scale (Schultz, 2002a), and measures of hedonic and eudaimonic wellbeing. Cross-cultural differences were found in a number of nature relatedness principal components, as well as differences in links between nature relatedness, spirituality, and wellbeing. In all four countries, gratitude formed a significant indirect path from nature relatedness to mental health and quality of life. The findings suggest that spiritual aspects of human-nature relationships may contribute to wellbeing across cultures.

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 score0.004
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.014
GPT teacher head0.294
Teacher spread0.280 · 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

Citations18
Published2023
Admission routes2
Has abstractyes

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