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Record W2121857997 · doi:10.1002/mar.20522

“It's not Easy Being Green”: Exploring Green Creeds, Green Deeds, and Internal Environmental Locus of Control

2012· article· en· W2121857997 on OpenAlexaff
Mark Cleveland, Maria Kalamas, Michel Laroche

Bibliographic record

VenuePsychology and Marketing · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsConcordia UniversityWestern University
Fundersnot available
KeywordsLocus of controlPsychologyStructural equation modelingConfirmatory factor analysisSocial psychologyConstruct (python library)Exploratory factor analysisEnvironmentalismControl (management)Order (exchange)Political scienceManagementBusinessLawDevelopmental psychologyEconomicsComputer scienceStatisticsPsychometricsMathematics

Abstract

fetched live from OpenAlex

ABSTRACT The authors report on the development of a novel construct, internal environmental locus of control (INELOC), which captures consumers’ multifaceted attitudes pertaining to personal responsibility towards and ability to affect environmental outcomes. Using data gathered from a sample of consumers, the linkages between INELOC and a wide array of environmental behaviors were investigated. Exploratory and confirmatory factor analyses revealed four first‐order dimensions (“green consumer,” “activism,” “advocate,” and “recycling attitudes”) embedded within a second‐order INELOC factor. Structural equations modeling techniques showed that INELOC was a strong positive predictor of many behaviors. However, the nature of the attitude–behavior relationship varied considerably across behavioral contexts, implying that people do not consistently behave in a proenvironmental manner. © 2012 Wiley Periodicals, Inc.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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

Citations199
Published2012
Admission routes1
Has abstractyes

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