Health Impacts of Climate Change in Vanuatu: An Assessment and Adaptation Action Plan
Bibliographic record
Abstract
Climate change is one of the greatest global challenges and Pacific island countries are particularly vulnerable due to, among other factors, their geography, demography and level of economic development. A Health Impact Assessment (HIA) framework was used as a basis for the consideration of the potential health impacts of changes in the climate on the population of Vanuatu, to assess the risks and propose a range of potential adaptive responses appropriate for Vanuatu. The HIA process involved the participation of a broad range of stakeholders including expert sector representatives in the areas of bio-physical, socio-economic, infrastructure, environmental diseases and food, who provided informed comment and input into the understanding of the potential health impacts and development of adaptation strategies. The risk associated with each of these impacts was assessed with the application of a qualitative process that considered both the consequences and the likelihood of each of the potential health impacts occurring. Potential adaptation strategies and actions were developed which could be used to mitigate the identified health impacts and provide responses which could be used by the various sectors in Vanuatu to contribute to future decision making processes associated with the health impacts of climate change.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".