Impacts of Climate Change and Hydropower Development on the Community Livelihoods in Sondu Miriu River Basin, Kenya
Bibliographic record
Abstract
Hydropower is sustainable and environmentally friendly source of energy worldwide. Driven by streamflow, it is vulnerable to climate change and land use change. The hydropower production from the two-existing run-of-river hydropower projects on the Sondu Miriu river are vulnerable to rainfall variability and requires proper understanding of the climate change trends and policies to support sustainable hydropower development and put in place strategies for building resilience for the local communities. The main objective of this paper was to examine the impacts of both the climate change and the hydropower development projects on the livelihoods of the community living within the Sondu Miriu River basin. Participatory methodologies involving administration of questionnaires at household level and focus group discussions with the local leaders and actors were applied to determine the impacts of climate change and the hydropower development on the community livelihoods within the basin. The socioeconomic status of the basin indicates that majority of the households (>59%) are poor and earn below 8 US dollars per day. The employment rate is extremely low with only 22% in formal employment. About 49% of the households still use wood fuel and charcoal as energy sources which is a threat to catchment conservation. Strengthening community resilience to climate change impacts is one of the benefits to be derived from the hydropower projects by supporting appropriate adaptation strategies within the existing policy framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".