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Record W2922822701 · doi:10.3390/su11061693

Accounting for Individual Differences in Connectedness to Nature: Personality and Gender Differences

2019· article· en· W2922822701 on OpenAlexaff
Annamaria Di Fabio, Marc A. Rosen

Bibliographic record

VenueSustainability · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsSocial connectednessAgreeablenessPsychologyBig Five personality traitsSocial psychologyPersonalityExtraversion and introversionSustainabilityConstruct (python library)Ecology

Abstract

fetched live from OpenAlex

In the psychology of sustainability and the sustainable development framework, regarding the specific focus on the natural environment, the construct of connectedness to nature is studied in depth for its potential for environmental management. The present research focuses on individual differences, examining the relationships between connectedness to nature and the Big Five personality traits in 459 Italian university students. This work analyzes whether gender differences emerge with respect to connectedness to nature, answering a more exploratory research question, since previous studies have not considered this aspect. The results show that agreeableness and extraversion are positively associated with connectedness to nature in Italian university students. No gender differences emerged with respect to connectedness to nature. Also, the relationship between connectedness to nature and personality traits was mainly found to be gender invariant. Future perspectives for research and intervention are offered in the psychology of sustainability and the sustainable development framework.

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)0.004
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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

Citations57
Published2019
Admission routes1
Has abstractyes

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