Geographic disparities and moral hazards in the predicted impacts of climate change on human populations
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.
Bibliographic record
Abstract
Aim It has been qualitatively understood for a long time that climate change will have widely varying effects on human well-being in different regions of the world. The spatial complexities underlying our relationship to climate and the geographical disparities in human demographic change have, however, precluded the development of global indices of the predicted regional impacts of climate change on humans. Humans will be most negatively affected by climate change in regions where populations are strongly dependent on climate and favourable climatic conditions decline. Here we use the relationship between the distribution of human population density and climate as a basis to develop the first global index of predicted impacts of climate change on human populations. Location Global. Methods We use spatially explicit models of the present relationship between human population density and climate along with forecasted climate change to predict climate vulnerabilities over the coming decades. We then globally represent regional disparities in human population dynamics estimated with our ecological niche model and with a demographic forecast and contrast these disparities with CO2 emissions data to quantitatively evaluate the notion of moral hazard in climate change policies. Results Strongly negative impacts of climate change are predicted in Central America, central South America, the Arabian Peninsula, Southeast Asia and much of Africa. Importantly, the regions of greatest vulnerability are generally distant from the high-latitude regions where the magnitude of climate change will be greatest. Furthermore, populations contributing the most to greenhouse gas emissions on a per capita basis are unlikely to experience the worst impacts of climate change, satisfying the conditions for a moral hazard in climate change policies. Main conclusions Regionalized analysis of relationships between distribution of human population density and climate provides a novel framework for developing global indices of human vulnerability to climate change. The predicted consequences of climate change on human populations are correlated with the factors causing climate change at the regional level, providing quantitative support for many qualitative statements found in international climate change assessments.
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 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it