Sustainable competitiveness of the cocoa sector in Ecuador: challenges of integrated socio-ecological governance
Bibliographic record
Abstract
The macro-economic context of cocoa is characterised by a worldwide growth of chocolate consumption, a sectoral industrial concentration, and a renewal of socio-ecological challenges for the production development. To remain competitive, cocoa-producing countries must follow new environmental and social standards. These standards lead to a reduction of the ecological footprint of cocoa due to deforestation, to a reduction in the use of pesticides, and to higher compliance with international labour standards. They also lead, in the expansion of the International Sustainable Development Goals, to modifying the distribution of value in the sectors for farmers, or to protecting the territories of indigenous people. These norms structure the notion of "inclusive competitiveness" and its translation into public policies or action strategies for actors in the cocoa sector. This paper uses a methodological approach developed within the framework of the European Union (Avadí et al. 2021 - VCA4D) that analyses agricultural value chains by combining economic, environmental and social indicators. In Ecuador, this approach is documented by two surveys of 40 actors from the value chain (producers, cooperatives, exporters, industrialists), and 20 institutional actors (ministerial support services, donors, project and program managers, research, certification institutions, etc.). The interviews were carried out in two phases in 2020 and 2021, respectively. This approach also mobilises an in-depth analysis of international secondary databases on the functioning of markets (IICCO, FAO, COLEACP, IFOAM), and national databases on the Ecuadorian cocoa sector and production costs. The results explain why, with an unfavourable production cost differential, Ecuador has improved its competitiveness indicators since 1997. They reveal a break in the trajectory in 2015, which implies a renewed policy of qualitative differentiation of Ecuadorian cocoa to move away from a commodity specialisation. These results highlight the risks of sectoral integration governed by a globalised industry. Moreover, they show the potential for competitiveness that can be mobilised by small producer organisations. Finally, they reveal how the increase in social-ecological impacts are more related to public institutions of governance of socio-organisational norms than to product certification. These results converge to document a globalised governance of investment regulation in the cocoa sector of developing countries. They clarify and debate the conditions for the development of cocoa production in the service of local populations by reducing the extensive exploitation of ecological resources. Keywords: Cocoa, Ecuador, Competitiveness, Socio-ecological, Innovation
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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 | 0.001 |
| 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".