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Record W4392171457 · doi:10.1017/sus.2024.5

Recentering evolution for sustainability science

2024· article· en· W4392171457 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

VenueGlobal Sustainability · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsUniversity of TorontoMcGill University
FundersUniversidad Nacional Autónoma de México
KeywordsSustainabilitySustainability scienceEnvironmental scienceSocial sustainabilityBiologyEcology

Abstract

fetched live from OpenAlex

Abstract Non-technical summary Evolutionary biology considers how organisms and populations change over multiple generations, and so is naturally focused on issues of sustainability through time. Yet, sustainability science rarely incorporates evolutionary thinking and most scientists and policy makers do not account for how evolutionary processes contribute to sustainability. Understanding the interplay between evolutionary processes and nature's contribution to people is key to sustaining life on Earth. Technical summary Evolution, the change in gene frequencies within populations, is a process of genetically based modification by descent, providing the raw material essential for adaptation to environmental change. Therefore, it is crucial that we understand evolutionary processes if we aim for a sustainable planet. We here contribute to this development by describing examples of contemporary, rapid evolutionary changes of concern for sustainability, specifically highlighting the global spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and how the evolutionary toolbox allowed tracking the origins and evolution of SARS-CoV-2 in real time and predicting potential future outbreaks. We also consider how urban development accelerates evolutionary processes such as altered phenotypic and physiological changes and the spread of infectious and zoonotic diseases. We show the importance of evolutionary concepts and techniques for public-health decision making. Many examples of the potential of evolutionary insights contributing to crucial sustainability challenges exist, including infectious and zoonotic diseases, ecosystem and human health, and conservation of natural resources. We thus join recent calls advocating for a stronger collaboration between evolutionary biologists and the sustainability community, increasing interdisciplinarity and the awareness about the knowledge of evolutionary processes for decision making and policies. Social media summary Evolution is fundamental to sustaining life on Earth and should be incorporated in sustainability measures and policies.

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)0.015
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0030.004
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.385
Teacher spread0.370 · 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