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Record W2131900519 · doi:10.1002/sres.2371

The Relationship between Systems Thinking and the New Ecological Paradigm

2015· article· en· W2131900519 on OpenAlexaff
Adam C. Davis, Mirella L. Stroink

Bibliographic record

VenueSystems Research and Behavioral Science · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsLakehead University
Fundersnot available
KeywordsEcological systems theorySystems thinkingEcologyPsychologySocial systemCognitionValue (mathematics)Paradigm shiftValue systemsBelief systemSociologyEpistemologySocial psychologySocial scienceComputer scienceBiology

Abstract

fetched live from OpenAlex

The goal of the present research was to examine the relationship between the cognitive paradigm systems thinking and an ecologically informed worldview, specifically the New Ecological Paradigm. One hundred and fifteen psychology undergraduate students completed an online questionnaire assessing systems thinking, ecological worldview, environmental value‐orientation, connectivity to nature, and environmental behaviors. Results demonstrated that systems thinkers possess a stronger ecological worldview and sense of connectivity with nature, harbour biospheric environmental values, and engage in more pro‐environmental behaviors than those scoring low on systems thinking. Furthermore, it was found that systems thinking both uniquely predicted and was predicted by the New Ecological Paradigm. Moreover, results demonstrated that systems thinkers are better able to acknowledge ‘system membership’ and possess a greater understanding of the characteristics of complex ecological systems and their mutual influence on social‐economic domains. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

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)0.005
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.718
GPT teacher head0.562
Teacher spread0.156 · 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

Citations121
Published2015
Admission routes1
Has abstractyes

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