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Record W4387491672 · doi:10.1016/j.heliyon.2023.e20544

Proposed solutions to anthropogenic climate change: A systematic literature review and a new way forward

2023· review· en· W4387491672 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHeliyon · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsClimate changeEnvironmental scienceManagement scienceEngineering ethicsEngineeringGeologyOceanography

Abstract

fetched live from OpenAlex

Humanity is now facing what may be the biggest challenge to its existence: irreversible climate change brought about by human activity. Our planet is in a state of emergency, and we only have a short window of time (7-8 years) to enact meaningful change. The goal of this systematic literature review is to summarize the peer-reviewed literature on proposed solutions to climate change in the last 20 years (2002-2022), and to propose a framework for a unified approach to solving this climate change crisis. Solutions reviewed include a transition toward use of renewable energy resources, reduced energy consumption, rethinking the global transport sector, and nature-based solutions. This review highlights one of the most important but overlooked pieces in the puzzle of solving the climate change problem - the gradual shift to a plant-based diet and global phaseout of factory (industrialized animal) farming, the most damaging and prolific form of animal agriculture. The gradual global phaseout of industrialized animal farming can be achieved by increasingly replacing animal meat and other animal products with plant-based products, ending government subsidies for animal-based meat, dairy, and eggs, and initiating taxes on such products. Failure to act will ultimately result in a scenario of irreversible climate change with widespread famine and disease, global devastation, climate refugees, and warfare. We therefore suggest an "All Life" approach, invoking the interconnectedness of all life forms on our planet. The logistics for achieving this include a global standardization of Environmental, Social, and Governance (ESG) or similar measures and the introduction of a regulatory body for verification of such measures. These approaches will help deliver environmental and sustainability benefits for our planet far beyond an immediate reduction in 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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.004

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 head0.051
GPT teacher head0.318
Teacher spread0.267 · 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