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Record W4393858242 · doi:10.1016/s2542-5196(24)00024-x

Advancing disability-inclusive climate research and action, climate justice, and climate-resilient development

2024· article· en· W4393858242 on OpenAlexaff
Penelope J. S. Stein, Michael Ashley Stein, Nora Groce, Maria Kett, Emmanuel Akyeampong, Willliam P Alford, Jayajit Chakraborty, Sheelagh Daniels-Mayes, Siri Eriksen, Anne Fracht, Luis Enrique Mafla Gallegos, Shaun Grech, Pratima Gurung, Asha Hans, Paul Harpur, Sébastien Jodoin, J. E. Lord, Setareki S. Macanawai, Charlotte McClain‐Nhlapo, Benyam Dawit Mezmur, Rhonda J. Moore, Yolanda Muñoz, Vikram Patel, Phuong Pham, Gérard Quinn, Sarah A Sadlier, Carmel Shachar, Matthew S. Smith, Lise Van Susteren

Bibliographic record

VenueThe Lancet Planetary Health · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsMcGill University
FundersWeatherhead Center for International Affairs, Harvard UniversityUniversity College LondonNorges Miljø- og Biovitenskapelige UniversitetHarvard University
KeywordsClimate justiceInclusion (mineral)Climate changePolitical sciencePsychological resiliencePolitical economy of climate changeDiversity (politics)Sustainable developmentEnvironmental resource managementEnvironmental planningEnvironmental ethicsSociologyGeographyPsychologySocial scienceEcologySocial psychologyEconomicsLaw

Abstract

fetched live from OpenAlex

Globally, more than 1 billion people with disabilities are disproportionately and differentially at risk from the climate crisis. Yet there is a notable absence of climate policy, programming, and research at the intersection of disability and climate change. Advancing climate justice urgently requires accelerated disability-inclusive climate action. We present pivotal research recommendations and guidance to advance disability-inclusive climate research and responses identified by a global interdisciplinary group of experts in disability, climate change, sustainable development, public health, environmental justice, humanitarianism, gender, Indigeneity, mental health, law, and planetary health. Climate-resilient development is a framework for enabling universal sustainable development. Advancing inclusive climate-resilient development requires a disability human rights approach that deepens understanding of how societal choices and actions-characterised by meaningful participation, inclusion, knowledge diversity in decision making, and co-design by and with people with disabilities and their representative organisations-build collective climate resilience benefiting disability communities and society at large while advancing planetary health.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.107
GPT teacher head0.415
Teacher spread0.308 · 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.

Study designObservational
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

Citations45
Published2024
Admission routes1
Has abstractyes

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