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Record W2079559446 · doi:10.1177/0013916508318748

The Nature Relatedness Scale

2008· article· en· W2079559446 on OpenAlexaff
Elizabeth K. Nisbet, John M. Zelenski, Steven A. Murphy

Bibliographic record

VenueEnvironment and Behavior · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologyConstruct (python library)Construct validityScale (ratio)DisconnectionPersonalitySocial psychologySample (material)Experience sampling methodReliability (semiconductor)Natural (archaeology)Cognitive psychologyDevelopmental psychologyPsychometricsGeographyCartographyComputer science

Abstract

fetched live from OpenAlex

Disconnection from the natural world may be contributing to our planet's destruction. The authors propose a new construct, Nature Relatedness (NR), and a scale that assesses the affective, cognitive, and experiential aspects of individuals' connection to nature. In Study 1, the authors explored the internal structure of the NR item responses in a sample of 831 participants using factor analysis. They tested the construct validity of NR with respect to an assortment of environmental and personality measures. In Study 2, they employed experience sampling methodology examining if NR people spend more time outdoors, in nature. Across studies, NR correlated with environmental scales, behavior, and frequency of time in nature, supporting the reliability and validity of NR, as well as the contribution of NR (over and above other measures) to environmental concern and behavior. The potential of NR as a useful method for investigating human-nature relationships and the processes underlying environmental concern and behaviors are discussed.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.005
GPT teacher head0.221
Teacher spread0.215 · 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 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

Citations1,884
Published2008
Admission routes1
Has abstractyes

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