Narrating changes, recalling memory: accumulation by dispossession in food systems of Indigenous communities at the extremes of Latin America
Bibliographic record
Abstract
Food feeds knowledge and practices through generations, sustaining biocultural memories. However, prevailing economic models and state policies have driven processes of accumulation by dispossession, defined as incremental social-ecological processes by which people lose their means of production and social reproduction. We conducted a cross-hemispherical study exploring food systems of Indigenous communities inhabiting forested landscapes in Latin America. We used mixed methods that included passive and participant observation, focus groups, free lists, food diaries, oral histories, and calendars in Mapuche communities from the Chilean Andes, and Tzotzil communities from Chiapas, Mexico. Food items and their preparations have changed in both locations. Both food systems show patterns of accumulation by dispossession associated with processes of colonial history, state policies, land privatization, soil depletion, and shifts in local food preferences. Despite these distant but comparable accumulation by dispossession processes, we advocate that biocultural memory remains linked to food-related experiences and sets the basis for dynamic and resilient local food systems going forward.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".