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Record W4389510688 · doi:10.55366/suse.v1i1.8

Advancing Sustainability and Social Justice in the Global South

2023· article· en· W4389510688 on OpenAlexaboutno aff
Adenike A. Akinsemolu

Bibliographic record

VenueSustainE · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental justiceSustainabilityPovertyIndigenousPolitical scienceEconomic JusticeEnvironmental degradationEnvironmental ethicsSustainable developmentHuman rightsDevelopment economicsSocial justiceGlobal justiceEconomic growthEnvironmental planningSociologyGeographyPolitical economyEcologyLawEconomics

Abstract

fetched live from OpenAlex

Harmful anthropogenic activities adversely affect Indigenous populations, such as the Inuit people and Nigeria’s Ogoni people. Environmental degradation disparately burdens such communities, thus making them to seek for environmental justice. Tribunals at all levels have affirmed that failing to safeguard the environment violates human rights, especially for Indigenous people who need a healthy environment, food, and access to resources to survive. The Global South continues to grapple with a plethora of issues, including ecological unsustainability, poverty, and inequality, but issues of justice are often disregarded in sustainability-oriented projects. Therefore, there is a need for countries in this region to integrate social justice into environmental sustainability. The concept of environmental justice traces its origins to the US during the 1980s when scholars used it to describe the unequal effect of industrial pollution on the country’s racial minorities. The idea has significantly blossomed during the last five decades, expanding historically and geographically to cover various global environmental struggles. This article explores why the concept of social justice has resonance and usefulness for advancing sustainability and why it is timely for the concept to be considered for the Global South. It delves into these issues with a specific focus on the Global South, examining case studies from various countries in the region and exploring key insights from the Global North.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.348
Teacher spread0.334 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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