Migration and Displacement Associated with Aridity, Drought, Heat, and Wildfires
Bibliographic record
Abstract
The present chapter focuses on migration and displacement associated with events that are directly linked to hotter air temperatures and/or an associated lack of moisture experienced at local and regional scales: droughts, increased aridity, desertification, heat, and wildfires. With the exception of wildfires – which share many characteristics comparable to rapid-onset extreme weather events – the hazards assessed in the present chapter are gradual in their onset and impacts. Their impacts accumulate with each passing week, month, and/or year, steadily eroding the water, food and/or livelihood security of households and communities. The slow rate of onset allows exposed populations an opportunity to adjust and adapt through means that do not require changes to existing mobility practices and patterns, sometimes referred to as in situ adaptation responses. It is only after hot and/or dry conditions persist beyond a particular threshold of duration and/or severity that in situ adaptations no longer prove to be sufficient and changes in migration decision-making and outcomes emerge.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 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".