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Environmental Crisis and Sustainable Development in South America

2025· reference-entry· en· W4410475269 on OpenAlexaboutno aff
Anabel Marín, Elisabeth Möhle, Ana Julia Aneise

Bibliographic record

VenueOxford Research Encyclopedia of Climate Science · 2025
Typereference-entry
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Technological Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsNatural resourceNatural resource economicsPovertySustainable developmentBusinessPopulationDevelopment economicsEconomicsEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Abstract South America has compelling reasons to address the climate and environmental crisis. First, the region is highly vulnerable to its impacts due to its economic reliance on natural resources and the susceptibility of its population. Addressing these vulnerabilities is crucial for the well-being of current and future generations. Second, as the global economy shifts toward more sustainable pathways to address the crises, South America has the potential to benefit economically by leveraging its clean energy matrix and abundant reserves of critical minerals, positioning itself as a key supplier in the global transition toward renewable energy and electric mobility. However, challenges such as poverty, inequality, and political and economic instability often divert attention and resources away from environmental priorities, constraining the region’s ability to fully embrace and implement comprehensive environmental policies. Integrating decarbonization efforts with economic diversification objectives could help address environmental and developmental challenges simultaneously, building the necessary internal support for difficult policies. This approach is essential to avoid a new “green resource curse,” which, in South America, would mean remaining limited to being providers of natural resources, but now for a decarbonizing global economy. This scenario could perpetuate historical and persistent social, environmental, and economic challenges. A major obstacle to green industrialization in the region is “structural path dependency”—a phenomenon that typically affects regions heavily reliant on a few low-complexity economic sectors, limiting their capacity to diversify into more complex products. To address this challenge, significant socioeconomic and political efforts are needed. Restricted resources, limited institutional capacities, and heavy dependence on powerful stakeholders, typically linked to carbon-intensive and environmentally damaging activities, hinder effective environmental governance, often leading to a “race to the bottom” where regulatory leniency is granted to attract large extractive investments. Despite the obstacles, external and internal forces are driving positive changes in the region. International pressures, such as border carbon adjustments and environmental standards, are encouraging governments and companies to adopt greener practices. The region is introducing innovations in sustainable agriculture and agroecology, and developing novel technological approaches in the extractive sector. Local movements, civil society organizations, and feminist groups have played a very important role, consistently advocating for better environmental and social outcomes and more democratic decision-making. Their demands have contributed to gradually strengthening environmental institutions. A recent milestone in this direction was the signing of the Escazú Agreement, aimed to improve public access to environmental information and justice, among other initiatives. The region is also gradually advancing in climate policies under the Paris Agreement, as well as in biodiversity protection programs under the Kunming-Montreal Framework. Three key areas of work for a just transformation in the region include: (a) strengthening state capacities for environmental management through essential institutional reforms that empower environmental and social authorities while ensuring comprehensive policy integration across key areas; (b) empowering civil society and local communities and supporting vulnerable groups affected by the transition, as justice in reforms is vital for legitimacy, especially given budget constraints and historical injustices; and (c) advancing diplomatic efforts to elevate global discussions on climate justice and reparations, which are essential for securing financial support and addressing the region’s pervasive sense of injustice.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.043
GPT teacher head0.290
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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