Explaining bioenergy: representations of jatropha in Kenya before and after disappointing results
Bibliographic record
Abstract
portrayed the crop as a 'sustainable biofuel' that was less threatening to food security and forests than other energy crops, creating a reputation that helped jatropha projects to multiply quickly throughout the global South. However, many jatropha initiatives failed to thrive and ultimately collapsed. This paper investigates how actors involved with jatropha in Kenya explained their visions of bioenergy at two points in time. In 2009, when many activities were beginning, I interviewed small-scale farmers, NGO staff, researchers, donors, government officials and members of the private sector about their expectations of jatropha as an energy crop. In late 2013, after jatropha activities in the country had dwindled, I re-interviewed many of the same individuals about their current views and their explanations of the events that had transpired since the initial fieldwork. Synthesizing these two sets of representations provides insight into how biofuel projects have been constructed, negotiated and renegotiated. Early hopes for jatropha rested on the belief that it could achieve many goals simultaneously, but when it failed to meet expectations proponents chose between two strategies: (1) 'unbundling' these goals to pursue separately the various aspirations they had initially attached to jatropha; and (2) seeking a new means of achieving the same bundle of goals. Understanding the choices made by jatropha actors in Kenya contributes to knowledge on the political ecology of biofuels and responsible innovation, and may signal patterns to come as even greater expectations are attached to multi-use feedstocks in pursuit of the bioeconomy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.016 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".