The Effects of Household Wealth on Adoption of Agricultural Related Climate Change Adaptation Strategies in Zambia
Bibliographic record
Abstract
Despite increased emphasis targeting climate change adaptation strategies towards the poorer sections of communities, few adoption studies assess the uptake of these practices by these groups in a systematic and comprehensive manner. In this study, we used a combination of participatory rapid approaches and quantitative principal component analysis to determine each household’s wealth status, and to assess the relationship between wealth and the adoption of various agricultural related climate change adaptation strategies. Evidence from a random sample of 1231 households across six districts of Zambia showed that the more well-endowed households than their poorly endowed counter parts, adopted most of the climate change adaptation strategies. The relatively well-endowed households had a high probability of 10.6%, 9.5%, 7.1%, and 5.5% to embrace crop rotation, minimum tillage, fertiliser trees and change crop varieties due to climate change, respectively, than their poorly endowed counter parts. Most, if not all of these strategies require some level of resource investment hence only those households who could afford such resources are most likely to adopt them. The influence of household resource endowment on the uptake of several climate change adaptation strategies call for the subsidising of the relatively poor endowed households to encourage adoption of these strategies among this category of farmers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".