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Record W2060915688 · doi:10.1007/s10113-014-0648-2

The status of climate change adaptation in Africa and Asia

2014· article· en· W2060915688 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRegional Environmental Change · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsMcGill University
FundersDepartment for International DevelopmentInternational Development Research Centre
KeywordsVulnerability (computing)Adaptation (eye)Climate changeDisadvantagedPolitical scienceDevelopment economicsIndigenousGrey literatureEconomic growthGeographyLivelihoodClimate change adaptationEnvironmental resource managementEconomicsEcologyAgriculture

Abstract

fetched live from OpenAlex

Adaptation is a key component of climate policy, yet we have limited and fragmented understanding of if and how adaptation is currently taking place. In this paper, we document and characterize the current status of adaptation in 47 vulnerable ‘hotspot’ nations in Asia and Africa, based on a systematic review of the peer-reviewed and grey literature, as well as policy documents, to extract evidence of adaptation initiatives. In total, 100 peer-reviewed articles, 161 grey literature documents, and 27 United Nations Framework Convention on Climate Change National Communications were reviewed, constituting 760 adaptation initiatives. Results indicate a significant increase in reported adaptations since 2006. Adaptations are primarily being reported from African and low-income countries, particularly those nations receiving adaptation funds, involve a combination of groundwork and more concrete adaptations to reduce vulnerability, and are primarily being driven by national governments, NGOs, and international institutions, with minimal involvement of lower levels of government or collaboration across nations. Gaps in our knowledge of adaptation policy and practice are particularly notable in North Africa and Central Asia, and there is limited evidence of adaptation initiatives being targeted at vulnerable populations including socioeconomically disadvantaged populations, children, indigenous peoples, and the elderly.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.113
GPT teacher head0.278
Teacher spread0.164 · 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