Valuing Pollination as an Ecosystem Services: The Case of Hand Pollination for Cocoa Production in Ghana
Bibliographic record
Abstract
The promotion of cocoa farm productivity has necessitated the intensification of input use with ensuing loss of natural pollinators. Ghana Cocoa Board’s (COCOBOD) remedy to declining pollinator population is addressed in the rolling out of hand pollination in the 2016/17 crop year. Applying contingent valuation on field data covering 608 farmers in five cocoa growing regions, we estimate the value of pollinator services to the cocoa industry in Ghana and farmers willingness to pay for the service. We find that cocoa farmers in Ghana are willing to pay for hand pollination to improve on their farm yields. Farmers averagely value pollinator services at $1.3 per acre of land. Extrapolated to cover all cultivated cocoa lands for 2017/18 crop year, the value of pollinator services to Ghana’s cocoa industry is averagely $6.1 million per annum. Hand pollination can improve cocoa farms yields given the statistically significant mean difference in yields between hand-pollinated and non-hand-pollinated farms. Having established the loss to the cocoa industry from pollinator decline and the need for effective pollination to support crop productivity, it is imperative for COCOBOD to ramp up strategies at preserving cocoa farm ecology to safe guard the industry.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".