Will the trade of Amazonian fruits help recover the Amazon forest? Sustainable consumption of Acai in Metro Vancouver
Bibliographic record
Abstract
Background: Extensive ranching and agriculture are among the leading drivers of deforestation and biodiversity loss in the Amazonia. Existing conservation instruments to change these practices such as results-based payments and REDD+ created institutional capacity but fell short in supporting a shift to sustainable agriculture. As a solution to this problem, Amazon countries have begun to promote the sustainable production of native fruits considering its increasing demand in the health food industry. \nResearch Questions: For the past 15 years, the Acai berry (Euterpe oleracea) has been one of the most in-demand Amazonian health fruits in North America. Agroforestry of Acai claims to have assisted in the ecological recovery of deforested Amazonian landscapes by providing stable rural livelihoods, whilst offering nutritional benefits to consumers. But, how “sustainably” engaged are Acai consumers in Metro Vancouver? Are they aware of the environmental and social impacts of the Amazonian products they consume? \nMethods: An assessment of attitudes towards the sustainable consumption of Acai products in Metro Vancouver is carried out through a Likert survey. I analyze major concerns on the social and environmental impacts in the sourcing of purchased Acai products. Responses are then correlated with demographic profiles of recruited consumers. Furthermore, a comparative analysis of eco-certifications and regulations applicable to Acai markets in North America and Europe offer an overview of the regulatory barriers and opportunities to develop market-based mechanisms to recover biodiverse contested landscapes. \nResults: Findings suggest that despite eco-certifications, Vancouverites are increasingly concerned about the effects that Acai products they consume have on their health and nature. Yet, they seem unaware of the social and environmental consequences of purchase decisions. \nContribution: This research provides insights on the sustainable consumption of healthy Amazonian products in Canada as an alternative to recover contested natural landscapes. Informed sustainable consumers and appropriate regulations facilitate the transition from conventional to biodiversity-centred food systems and diets. Such conversion contributes to solving biodiversity loss, rural inequality and nutritional problems of human’s growing population.
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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".