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Record W2551388071 · doi:10.3138/ijcs.53.61

Environmental Skepticism and Its Impact on Environmental Behaviour in Canada

2016· article· en· W2551388071 on OpenAlexaffvenueabout
Min Zhou

Bibliographic record

VenueInternational Journal of Canadian Studies · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSkepticismReligiosityIdeologyEnvironmentalismEnvironmental ethicsPoliticsStructural equation modelingEnvironmental impact assessmentSustainable developmentPolitical scienceSociologyPsychologySocial psychologyEpistemologyLaw

Abstract

fetched live from OpenAlex

Environmental skepticism refers to doubt about the authenticity or severity of environmental threats facing the world today. Using Canadian data from the International Social Survey Program conducted in 2011 and structural equation modelling, this study explores social determinants of environmental skepticism and its impact on environmental behaviour. Cognitive bias, generalized trust, and competing concern theories are found to be effective in explaining why some Canadians are more skeptical than others. Certain worldviews (a high level of religiosity, conservative political ideology), lack of trust in general society, and competing non-environmental concerns are three key factors underlying environmental skepticism in Canada. This study further finds that environmental skepticism has a real impact on individuals' environmental behaviour. It inhibits both the adoption of environmentally friendly lifestyles and engagement in environmentalist activism. Environmental skepticism thus can be a serious barrier to building an environmentally sustainable society in Canada.

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)0.007
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 score0.072
Threshold uncertainty score0.525

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0070.002
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0010.002
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 head0.008
GPT teacher head0.263
Teacher spread0.254 · 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

Citations4
Published2016
Admission routes3
Has abstractyes

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