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Record W4313588808 · doi:10.3389/fenvs.2022.1019904

Engaging faith-based communities in pro-environmental behavior using soft regulations: The case of single-use plastics

2023· article· en· W4313588808 on OpenAlexaff
Dan Kaufmann, Ariel Tikotsky, Tanhum Yoreh, Anat Tchetchik

Bibliographic record

VenueFrontiers in Environmental Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNudge theoryRespondentFraming (construction)Social psychologyPopulationFaithPublic economicsNormativeFraming effectPsychologyEconomicsPersuasionSociologyPolitical scienceDemographyLawEngineering

Abstract

fetched live from OpenAlex

The consumption of single-use plastics, such as disposable tableware (DTW), conveys a high benefit-cost ratio for consumers while having large environmental externalities. To encourage consumers to reduce their use of DTWs, governments could use small and non-coercive changes in people’s decision-making environments (nudges). This study focuses on the Israeli ultra-Orthodox communities a secluded population group that grows much faster- and consumes much more DTW than the rest of the Israeli population. Employing a quasi-representative sample (N = 450) of this population, this study conducted a discrete-choice experiment that presents the respondent with alternative options to reduce DTW. Two kinds of Nudges–framing and social norms–were utilized. The effectiveness of these Nudges in promoting PEB among faith-based communities has received little attention in previous studies. As another contribution to the literature, this paper also integrates latent constructs such as the respondents’ environmental attitudes and level of conservativeness. 46% of the respondents chose to opt-out whereas 29%, 14%, and 11% chose ‘1-day’, ‘2-days’, and ‘3-days’ per week avoiding DTW, respectively. Social norms, framings, and environmental attitudes had a significant mediating effect, with framing being associated with the highest effect on intentions to reduce DTW, i.e., a willingness to give up 0.31 USD per family member per month, compared to 0.07 USD for an increase in the description of the social norm. The results suggest that Nudges can enhance policies aimed at encouraging pro-environmental behavior among faith-based communities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.006
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.258
Teacher spread0.230 · 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 teacher head, not a consensus.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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