Migration as an Adaptation Strategy to Climate Change: Influencing Factors in North-western Ghana
Bibliographic record
Abstract
Climate change has attracted the attention of all stakeholders, ranging from individuals in the household through to global organisations in the international community. As an inevitable phenomenon at the moment, adaptation is the key response to minimising the unfavourable effects of climate change. While there are several adaptation strategies, rural areas mostly use migration as an ultimate and most reliable option. Rural migration in Ghana is mostly from the north to the south. This paper examines the factors that influence individuals and households’ decision to use migration as an adaptation strategy to climate change effects in North-western Ghana. Data was collected using household questionnaire in four communities and analysed using statistical package for social science, version 20.0. The study established that although there are other reasons for migration, it is used essentially as an adaptation strategy to the effects of climate change on livelihood. The study concludes that the debate on climate change and migration should no longer be whether climate change causes human migration but how the effects of climate change influence migrants’ resolve to migrate as an adaptation strategy. Such an analysis allows policy makers to find practical adaptive capacity measures that can offset the challenges at the original homes of migrants.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| 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".