Socio-economics of Acai Production in Rural Communities in the Brazilian Amazon: A Case Study in the Municipality of Igarapé-Miri, State of Pará
Bibliographic record
Abstract
The Acai, a fruit of the Acai tree (Euterpe oleracea Mart.), is one of the main foods consumed by the riverside communities in the Brazilian Amazon. In addition, it has become the main source of income of these small producers as its consumption has widely expanded since the 1990s due to the recognition of its properties as an energetic and functional food. In order to analyze the production system and the socioeconomic changes that occurred in rural communities whose economical support is from the management of the Acai tree, a case study was carried out in two communities on the island of Mamangal, in the municipality of Igarapé-Miri, in the state of Pará, Brazilian Amazon. Fifty-two semistructured questionnaires were applied to the Acai farming families in these communities located in the municipality in the largest Brazilian producer of this fruit. The main transformations observed in the assessed communities, especially since the last decade, were influenced by the access to electric energy and the expansion of income from the Acai that made possible the expansion of the acquisition of durable consumer goods that even contributed to diversifying the diet of those farmers. Some of the difficulties faced by Acai production are the lack of technical assistance and rural extension services as well in addition to the strong dependence of the communities on the income generated by the Acai.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".