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Record W4391285717 · doi:10.16995/zygon.10959

Pathways to Equity in Addressing Climate Change: A Bahá’í Perspective

2024· article· en· W4391285717 on OpenAlexaff
Robert Sarracino, Margery Dixon

Bibliographic record

VenueZygon® · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Ecology, and Ethics
Canadian institutionsCentre For Cold Ocean Resources EngineeringMemorial University of Newfoundland
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

According to current scientific consensus, anthropogenic climate change has become one of the most serious existential threats to human civilization. In the latter half of the nineteenth century, Bahá’u’lláh warned of the dangers inherent in the unbridled advancement of material civilization if a parallel advance in the moral and spiritual dimensions of civilization were neglected.This article outlines a framework with three components for dealing with the crisis of anthropogenic climate change. The first component is to embrace justice and equity, rooted in an awareness of the essential oneness and wholeness of the human race. The second is the full embrace of sound science. The third is consultation at all levels of society regarding the technological and social measures to be taken, in which all have a voice and participate in forging solutions.It then outlines Bahá’í approaches to climate change in light of this framework. It first profiles the worldwide Bahá’í community, then discusses the concept of the three protagonists in the civilization-building process, and finally outlines the framework for action, which characterizes Bahá’í work at the neighborhood and community level.

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)0.006
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.027
Scholarly communication0.0150.010
Open science0.0020.012
Research integrity0.0070.008
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 head0.267
GPT teacher head0.482
Teacher spread0.215 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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