Bales and Balance : A Review of the Methods Used to Assess the Economic Impact of Bt Cotton on Farmers in Developing Economies
Bibliographic record
Abstract
We assess 47 peer-reviewed articles that have applied stated economics methods to measure the farm-level impacts of Bt cotton in developing agriculture from 1996. We focus on methods, although findings are also contrasted and compared in qualitative terms. The central research question assessed by the articles reviewed is: what are the current and potential advantages of transgenic cotton with respect to yield, pesticide use, input cost, revenue and/or profits at the farm-level, by farm type, and geographical region? We find that, while the evidence is promising, the balance sheet remains inconclusive in part because of some methodological limitations and in part because institutional and political context, which is mutable and often ignored, shapes economic impacts, especially over the longerterm. Most often, the contextual factors that influence whether a new variety succeeds or fails are more critical than whether yield advantages can be demonstrated in on-farm trials.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".