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Record W2588149485 · doi:10.1017/aee.2017.1

Exploring the Relations Between Childhood Experiences in Nature and Young Adults’ Environmental Attitudes and Behaviours

2017· article· en· W2588149485 on OpenAlexaff
Catherine Broom

Bibliographic record

VenueAustralian Journal of Environmental Education · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental consciousnessPsychologyConsciousnessIdentity (music)Natural (archaeology)Early childhoodDevelopmental psychologySocial psychologyProject commissioningSociologyPublishingAestheticsPolitical science

Abstract

fetched live from OpenAlex

Abstract This article presents the findings of a research study with young adults who explored the connections between their early childhood experiences in nature and their attitudes and actions towards the environment in adulthood. Drawing on E. Wilson's (1984) work, environmental or ecological consciousness is theorised to connect to ecological identity and relates to an individual's deep reflection on, connection to, and engagement with the natural environment. The study's survey tool invited young adults to select various options that described their experiences in nature as children and their views of, and actions towards, the environment in the present. The findings illustrated connections between childhood experiences in nature and later views of, and actions towards, the environment. The correlations between expressed views about caring for the environment and environmentally friendly actions were surprising, however, as actions did not necessarily align with beliefs. The article concludes with recommendations based on the findings, outlining how positive attitudes and actions towards the environment may be fostered in childhood.

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)0.002
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.280
Teacher spread0.260 · 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

Citations99
Published2017
Admission routes1
Has abstractyes

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