Dams, Displacement, and Perceptions of Development: A Case from Rio Negro, Guatemala.
Bibliographic record
Abstract
Guatemala's history is plagued with development' projects that result in displacement, violence, and increased marginalization of its Indigenous and non-Indigenous populations. In order to make way for development initiatives such as the production of coffee, bananas, and sugar cane the extraction of metals such as gold and nickel or, in this specific case, the construction of a large hydroelectric dam, the land-based, predominately Maya farmers, or campesinos, are systematically uprooted from the lands of their birth, and launched into uncertainty. Using the case of the Chixoy Hydroelectric Dam, built from 1978-1983, this thesis examines the effects of displacement on the former residents of Rio Negro, a community which endured a series of massacres by the military and paramilitary due to its resistant stance on forced removal. Through the use of open-ended interview discussions, or testimonies, as well as other qualitative methods, I attempt to illuminate this specific incident of displacement and violence, and discuss the outcomes thirty years later. My findings, based on fieldwork conducted January through April 2009, suggest that the majority of survivors from the Rio Negro massacres are still adversely affected from the destruction of their families and livelihoods, and that the return to a more self-determined and traditional Maya-Achi way of life is crucial for personal and community rehabilitation. I conclude that despite this incident occurring in unique circumstances, and at the height of the internal conflict, the same struggles over land and rights continue into the present--and if policies are left unchanged, clashes of this nature will only increase in time. --P. ii.
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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 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".