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Record W2944531179 · doi:10.24043/isj.80

Community-based adaptation to climate change: lessons from Tanna Island, Vanuatu

2019· article· en· W2944531179 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueIsland Studies Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsAdaptation (eye)Climate changeClimate change adaptationGeographyOceanographyPsychologyGeologyNeuroscience

Abstract

fetched live from OpenAlex

Community-based adaptation has gained significant international attention as a way for communities to respond to the increasing threats and complex pressures posed by climate change. This bottom-up strategy represents an alternative to the prolonged reliance on, and widespread ineffectiveness of, mitigation methods to halt climate change, in addition to the exacerbation of vulnerability resulting from top-down adaptation approaches. Yet despite the promises of this alternative approach, the efficacy of community-based adaptation remains unknown. Its potential to reduce vulnerability within communities remains a significant gap in knowledge, largely due to limited participatory evaluations with those directly affected by these initiatives, to determine the success and failure of project design, implementation, outcomes and long-term impact. This paper seeks to close this gap by undertaking an in-depth evaluation of multiple community-based adaptation projects in Tanna Island, Vanuatu and exploring community attitudes and behavioural changes. This study found that future community-based adaptation should integrate contextual specificities and gender equality frameworks into community-based adaptation design and implementation, as well as recognise and complement characteristics of local resilience and innovation. In doing this, the critical importance of looking beyond assumptions of Small Island Developing States (SIDS) as homogenous, primarily vulnerable to climate change and lacking resilience, was also recognised.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
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 head0.277
GPT teacher head0.403
Teacher spread0.126 · 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