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Record W3094607757 · doi:10.1145/3415199

Religion and Sustainability

2020· article· en· W3094607757 on OpenAlexafffund
Mohammad Rashidujjaman Rifat, Toha Toriq, Syed Ishtiaque Ahmed

Bibliographic record

VenueProceedings of the ACM on Human-Computer Interaction · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsPersuasionScholarshipReligiositySociologySpiritualityIslamSustainabilityEnvironmental ethicsEpistemologySociology of religionScope (computer science)CriticismSocial scienceSocial psychologyPolitical sciencePsychologyLawPhilosophyEcologyTheology

Abstract

fetched live from OpenAlex

While persuasion has often been considered an important design tool for achieving sustainable behavior, a growing scholarship is criticizing it for its narrow focus on individuals and an overarching economic worldview. This criticism is often based on the limitations of economic-rationales that many persuasive design efforts hold and cannot fully capture the values of people who reside outside the modern scientific world - especially where values originate from and are shaped by religiosity and spirituality. We join this discourse and argue that such a narrow view of persuasion sidelines the theological roots. Based on our six-month long ethnography with the Islamic communities in a Bangladeshi city, Kushtia, we describe how 'motivation' and 'habit' are built there - two of the basic components of persuasion. Drawing from a rich body of literature on the sociology of religions and theology, we highlight how Islamic values are closely tied to the idea of persuasion and reflect a vision of sustainable living. We further discuss how such a deeper understanding of religious values can help design for sustainable living and broaden the scope of CSCW literature in the various domains.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.022
GPT teacher head0.292
Teacher spread0.271 · 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 designNot applicable
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

Citations55
Published2020
Admission routes2
Has abstractyes

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Same venueProceedings of the ACM on Human-Computer InteractionSame topicEnvironmental Education and SustainabilityFrench-language works237,207