Sustainability trade-offs for equity and climate interventions in global food systems: The case of cocoa in Ghana
Bibliographic record
Abstract
Despite widespread attempts to ‘eat local,’ many of the lifestyle factors in the Global North rely on the production of agrifood commodities that can only be grown in tropical ecosystems, far from the dominant geographies of consumption. Chocolate, coffee, and palm oil represent a handful of consumer goods that are described as ‘tropical forest risk commodities,’  whose production threatens some of the last remaining biodiversity hotspots and stable carbon sinks. This research assesses the trade-offs between dominant approaches to poverty reduction in tropical forest landscapes – regions where global land use change is concentrated as forests are converted to agrifood commodity production areas to produce consumer goods that are core to global food systems. After Côte d’Ivoire, Ghana is the second largest exporter of cocoa (the main ingredient in chocolate). Ghana’s economy is highly cocoa-dependent, and cocoa provides livelihoods for about a quarter of the population, especially in rural areas where alternative incomes are limited. Although the cocoa sector contributed an estimated US$2.71 billion in government revenues in 2017, many cocoa producers live below the national poverty line.Policy responses to balance the trade-offs between global food production, climate change, and socioeconomic development have recently come to the fore in Ghana – the world’s second largest producer of cocoa. In 2019, the Government of Ghana introduced the Living Income Differential (LID), which requires buyers to pay an additional US$400 per ton of cocoa on top of the floor price. With low farmer incomes identified as a critical driver of multiple sustainability issues in Ghana’s cocoa sector, this differential is meant to be directly transferred to cocoa farmers in response to the persistent challenge of poverty in cocoa farming communities. Using the Q methodology, we engaged over 50 stakeholders from various levels (international policy experts, cocoa sector stakeholders in Ghana, and cocoa farmers) to understand how LID is perceived, including its potential to transform the rural poverty complex embedded in Ghana’s cocoa supply chain. While the LID is lauded for increasing producer price across the board, our findings indicate that the lack of regard for farmer diversity (i.e., tenure rights, sharecroppers, and caretakers), farm size, and land management strategies (agroforestry versus clearing forest to establish farms) risks undermining the ability of this pricing mechanism to reduce farmer poverty as a way to foster sustainability in the sector. Further, the LID is siloed from on-going sustainability governance efforts in the sector, such as zero deforestation cocoa. If the LID is delivered to farmers across the board without any quid pro quo for how cocoa is produced, the policy’s unintended consequences may include increasing deforestation in the short term, while lowering the world market price of cocoa in the long term as cocoa supply increases. We conclude with policy implications on why different perspectives matter in managing sustainability trade-offs in deforestation frontiers. This study provides important insights for understanding how to achieve multiple sustainability goals together.
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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 | 0.001 | 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 | 0.001 |
| 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".