Understanding pastoralist adaptations to drought via games and choice experiments: field testing among Borana communities
Bibliographic record
Abstract
Transhumant and nomadic pastoralism in arid and semi-arid spaces from West through Central, East, and Southern Africa is regarded as critical to regional system resilience and food security. Although pastoral systems are highly adapted and adaptive to uncertainty and change, recent decades of severe climatic events and increasing resource pressure are pushing pastoral systems to adopt novel norms and practices. Importantly, forage residue conservation and private forage enclosures are becoming important practices among herders and non-herders alike. As one part of considering the relevance of these responses in shaping the future trajectory of transhumant pastoralism, we developed a multi-part intervention for measuring and observing preferences in pastoral systems, including a novel experimental game called GreenReserve, and tested it in Borana communities in northern Kenya. We found that GreenReserve captured dimensions of human-environment dilemmas faced by pastoralists, and shifted preferences around herd size, losses, and the use of time, as measured through a repeated discrete choice experiment. We found game groups with younger players and with more female players to include more exploration of pastoral adaptations such as the use of grass reserves and the harvesting of grass, as well as to have less conflict within the game. We also observed both preferences as well as game strategy to shift along the length of the study: as the region moved further into a drought and failed short rainy season, players were more conscious of large herds, bad rainfall-year losses, and made better use of reserves in game play, though it was beyond the scope of the current study to determine causality. Future research is needed to unpack the mechanisms underlying the variations and possible shift in preferences and subsequently help identify entry points for targeted interventions (including agricultural extension services) to support pastoral communities in climate change adaptation. Further, these first fieldwork findings suggest two key dimensions for expanded work beyond this study to identify whether mixed methods approaches such as this aid experiential learning in agriculture contexts.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".