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Record W4394013002 · doi:10.1111/bjso.12743

Egoistic value is positively associated with pro‐environmental attitude and behaviour when the environmental problems are psychologically close

2024· article· en· W4394013002 on OpenAlexaff
Xiaobin Lou, Liman Man Wai Li, Kenichi Ito

Bibliographic record

VenueBritish Journal of Social Psychology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Lethbridge
FundersEducation University of Hong Kong
KeywordsPsychologyValue (mathematics)Social psychologyAssociation (psychology)Relation (database)Environmental pollutionGeography

Abstract

fetched live from OpenAlex

Egoistic value is conceptualized as anti-environmental in many environmental value theories, yet contradictory evidence exists for its relation with pro-environmental attitude and behaviour. To provide insights into these inconsistent findings, this research examined the moderating role of the psychological distance of environmental problems on their relationship. Across one cross-sectional survey study (1008 community participants from the United States) and one World Values Survey study (66,704 nationally representative participants from 46 countries/regions), results converged in showing that psychological distance of environmental problems (i.e. climate change and local pollution) moderated the relationship between egoistic value and pro-environmental attitude and behaviour. Their association became more positive as that psychological distance got closer. Different patterns were observed for altruistic and biospheric values. These findings highlight the potential pro-environmental utility of egoistic value and the importance of paying attention to contexts when theorizing its relation with pro-environmental attitude and behaviour.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.277
Teacher spread0.265 · 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.

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

Citations27
Published2024
Admission routes1
Has abstractyes

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