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Record W2946796083 · doi:10.3968/10878

Traditional African Ethical Perspective on Climate Change

2019· article· en· W2946796083 on OpenAlexvenueno aff
Onyibor Marcel Ikechukwu Sunday, Onwu Inya

Bibliographic record

VenueCanadian social science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Ecology, and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental ethicsEnvironmentalismReductionismPerspective (graphical)SociologySustainable developmentClimate changeGlobal warmingPolitical scienceEcologyEpistemologyLawPhilosophyPolitics

Abstract

fetched live from OpenAlex

This paper argues that a major contributory factor to climate change is human activities, and an effective solution requires strong philosophic bedrock, which we propose should be hinged on the tenets of traditional African ethical environmental conservation and principles of deep ecology. Our research questions are what is the spirit of African countries’ public policies and mitigation strategies for climate change? What is the philosophy of African scientific and environmental exploration, as well as its industrial revivalism? Is it apathetic material reductionism of the western industrial revolution or an empathetic environmentalism? Our theoretical solution explores the traditional African ethical recognition of the equal intrinsic worth of all biota regardless of human wants or needs, as well as the interconnectedness of human beings with the environment in all its plenitude. The paper thematically harnesses the close link between the traditional African ethical environmental concern with Aldo Leopold “land ethic” as an effective and sustainable solution to global warming.

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)0.004
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 score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.022
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0030.004
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 head0.088
GPT teacher head0.355
Teacher spread0.268 · 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
Published2019
Admission routes1
Has abstractyes

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