Contestation, conflict and claims-making around the Lake Turkana Wind Power windfarm, northern Kenya
Bibliographic record
Abstract
• We assess local perspectives of the Lake Turkana Wind Power (LTWP) project in Kenya, Africa’s largest windfarm to date. • Local framings of the LTWP are a critique of the project’s governance and elevation of gatekeepers who steered benefits. • Consultation processes are felt to have quieted the voices of many residents in a way that excluded many from benefitting. • Local framings and strategies can be considered a means of engagement and way to forge connections with public authorities. • Local meanings and practices redefine large projects in ways that challenge developer and state governance of everyday lives. Investment in large-scale renewable-energy projects has risen significantly as governments focus on green energy solutions. The general view is that renewable energy investments are beneficial, increasing national energy production from renewable sources and contributing to economic growth. However, the benefits for communities near project sites can be unclear, with less emphasis placed on the impacts on social cohesion or the rights of local populations. This paper contributes to discussions about community perspectives and responses to large land and resource based investments, stressing the role of local agency. Using the example of the Lake Turkana Wind Power (LTWP) project in northern Kenya, it examines how various stakeholders involved with specific resource-based investments perceive and challenge the development process and the distribution of project benefits and harms. It employs an ‘intersecting methodologies’ approach that includes community-based participatory research (CBPR), participatory video, and qualitative and ethnographic methods, conducted in small settlements around the LTWP area between 2017 and 2019. As the largest single private investment in Kenya’s history, life remains insecure for many residents near the LTWP wind farm. By revealing different local perspectives, the paper outlines the broader impacts and forms of contentious politics related to the LTWP project. The study finds that community strategies to seek recognition and associated rights highlight deeper conflicts involving governance and authority concerning everyday lives and livelihoods. Local agency underscores the limitations of efforts to formalize rights within a statutory legal and regulatory framework and other processes through which community stakeholders assert their inclusion in large-scale investments.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".