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Record W2883940547 · doi:10.1177/0013916518783241

The Behavior-Attitude Relationship and Satisfaction in Proenvironmental Behavior

2018· article· en· W2883940547 on OpenAlexaff
Myriam Ertz, Emine Sarigöllü

Bibliographic record

VenueEnvironment and Behavior · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsMcGill UniversityUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsPsychologyCognitive dissonanceSocial psychologyMediationConceptualizationExpectancy theoryPerceptionPerspective (graphical)Attitude changeAttitude

Abstract

fetched live from OpenAlex

Past research on environmentally sustainable behaviors has focused on the impact of a wide array of psychological factors, such as values, attitudes, norms, motivation, or perceptions, on behavior. The aim of this article is to study an alternative perspective by focusing on the effect of behavior on attitude, instead of the opposite, and by examining the mediation of satisfaction on that relationship. Drawing on both the self-perception and cognitive dissonance theories, we demonstrate that the expectancy disconfirmation model illuminates the conditions under which the past behavior-attitude link may improve. An online study with 409 U.S. citizens revealed that satisfaction mediates the positive behavior-attitude relationship, while this is not the case for the attitude-behavior relation. Our results also highlight the importance of multidimensional conceptualization for both proenvironmental behavior (PEB) and attitudes toward PEB, while providing useful guidelines for practitioners and policy makers.

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)0.011
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 score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.012
GPT teacher head0.261
Teacher spread0.248 · 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

Citations62
Published2018
Admission routes1
Has abstractyes

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