“Everyone decided to declare war on the forest”: between territorial peace and pacification in the Colombian Andean-Amazon
Bibliographic record
Abstract
In post-peace agreement Colombia, everyone declared war on the forest. In the Putumayo region, these wars take their own particular forms. Scientifically, the Putumayo is described as an Andean-Amazonic rainforest. For the indigenous and local inhabitants of the Putumayo, it is the Andean-Amazonic selva. We present three wars on the forest with material and discursive specificities and critically distinguish those that inherently involve violence from the ones that do not. We draw on a mix of empirical material to analyze how the wars on the forest have manifested in the Andean-Amazon. We find that both deforestation and the responses to combat it are two wars on the forest with one thing in common: violence. We also find that the selva is a territorialized political proposal with its own discursive and material elements. Drawing on the concept of territorial peace, we discuss the ambivalence of peacebuilding in relation to violence because it both legitimizes the continuation of violent wars on the forest while providing openings for territorial defense projects. This approach provides analytical avenues to observe the differences between peace and pacification. We contend that violence is incompatible with peace but not with pacification. Further, peace and pacification efforts can coexist under the discursive guise of peacebuilding. We show that peace requires the absence of violence but cannot be defined as the absence of violence alone, for such an understanding cannot distinguish a peaceful context’s territorial relations from those of a pacified context.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".