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Record W1970594193 · doi:10.1177/0013916503035004003

Further Validation of the Motivation Toward the Environment Scale

2003· article· en· W1970594193 on OpenAlexaff
Mark A. Villacorta, Richard Koestner, Natasha Lekes

Bibliographic record

VenueEnvironment and Behavior · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsMcGill University
Fundersnot available
KeywordsScale (ratio)Social psychologyPsychologyDiscriminant validityValue (mathematics)Life styleStyle (visual arts)Applied psychologyDevelopmental psychologyComputer scienceGeographyPsychometrics

Abstract

fetched live from OpenAlex

A study was conducted to further validate the Motivation Toward the Environment Scale (MTES). Results confirmed both the convergent and discriminant validity of the MTES by showing that peer reports corresponded to self-reports of environmental self-regulation and that environmental self-regulation was relatively distinct from self-regulation in academic and political domains. Results also pointed to some possible sources of autonomous self-regulation. Individuals were more likely to engage in autonomous environmental behaviors if (a) their parents had shown an interest in their developing attitudes about the environment, (b) their peers supported their freedom to make decisions about the environment, and (c) they had already developed life aspirations such as concern for their community. Finally, results confirmed the adaptive value of developing an autonomous regulatory style toward environmental activities. Thus, autonomous individuals were shown to report stable proenvironmental attitudes over time, a greater number of environmental behaviors, and higher levels of well-being.

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)0.011
metaresearch head score (Gemma)0.020
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 score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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

Citations108
Published2003
Admission routes1
Has abstractyes

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