The green economy as plantation ecology: When dehumanization and ecological simplification go 'green
Bibliographic record
Abstract
The green economy is proposed as a solution to address growing and potentially irreversible ecological crises. But what happens when environmental solutions are premised on the same logics of brutal simplification and dehumanization that sustain and reinforce systems of oppression and ecological breakdown? In this article, we describe the transformation of the biophysical landscape of the planet into replicable blueprints of the plantation plot. The plantation as a colonial-era organizational template is an ongoing ecological process premised on disciplining bodies and landscapes into efficient, predictable, calculable, and controllable plots to optimize commodity production and is dependent on racialized and gendered processes of dehumanization. The visible cultural, physical, aesthetic, and political singularity of the plot, under the guise of objectivity and neutrality, permits a tangible depiction of the way ecological breakdown takes place. We interrogate the notion of "greening" as a strategy to combat the unintended impacts of colonial plantation ecology, arguing that such tactics further reinforce the template of plantation ecology rather than dismantle it. We first conceptualize the historical plantation and its biophysical, cognitive, and corporeal organizational principles. We then offer examples of "greening" as new, more inclusive (but equally detrimental) forms of plantation logics, and crucially identify how these extensions of plantation logic get co-opted by resistance agents, from social movements to disease and pestilence. We consider sustainability certifications of palm oil through the Roundtable on Sustainable Palm Oil (RSPO) in Colombia and compensatory afforestation programs designed to offset forest destruction through monoculture plantations in India. We conclude by highlighting how abolition ecologies can serve as an antidote to plantation logic and highlight necessary relationships of self-reflexivity, repair and collective solidarity required to disinvest in plantation ecology.
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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 | 0.004 | 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 | 0.006 | 0.073 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".