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Record W4226360795 · doi:10.1177/00139165211065008

Access to Environmental Cognitive Alternatives Predicts Pro-Environmental Activist Behavior

2021· article· en· W4226360795 on OpenAlexaffabout
Joshua D. Wright, Michael T. Schmitt, Caroline M.L. Mackay

Bibliographic record

VenueEnvironment and Behavior · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsStatus quoSocial psychologyPsychologyCognitionAction (physics)Environmental communicationIdentity (music)Political sciencePublic relationsLaw

Abstract

fetched live from OpenAlex

We expand on the plausible role of access to cognitive alternatives to the environmental status quo (i.e., the ability of people to imagine what a sustainable relationship with nature would look like) in motivating pro-environmental collective action. Using a representative sample of Canadians on age, gender, and ethnicity ( N = 1,029) we evaluate the associations between access to environmental cognitive alternatives, politicized environmental identity, and willingness to engage in pro-environmental activist behavior. Additionally, we move beyond self-reported behavior by giving participants the opportunity to write and sign a pro-environmental letter to the Canadian Minister of the Environment and Climate Change. Our results suggest that access to cognitive alternatives is associated with stronger politicized environmental identity, greater willingness to engage in pro-environmental activist behavior, and increased likelihood of writing and signing a pro-environmental letter. All methods and analyses follow our preregistration and all materials and data are openly available.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.205
Threshold uncertainty score0.407

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.018
GPT teacher head0.287
Teacher spread0.270 · 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

Citations42
Published2021
Admission routes2
Has abstractyes

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