Visualizing Canada in Central America: radical cartography and transnational connections in the green extractivist transition
Bibliographic record
Abstract
This paper mobilizes radical cartographic projects to explore the participation of Canada within green extractivism in Central America. The transition to a green capitalist economy built on alternative energy sources is well underway across the region of Central America, but the multiple forms of dispossession and agrarian change associated with the transition have generated significant harm for surrounding communities. This paper highlights the extractivist logic of supposedly renewable energy by pairing the literature on green extractivism with findings from fieldwork with rural communities surrounding energy and infrastructure projects in Costa Rica and Panama. In doing so, both the literature review and research findings connect with projects of radical cartography, which aim to subvert state and corporate mapping through grassroots projects of art-based resistance. Following an exploration of the Beehive Collective’s Mesoamérica Resiste! poster, the paper presents a pair of original maps and a series of stories, in order to demonstrate the communicative power and theoretical potential of radical cartography. The stories presented here were collected over five months of fieldwork in Costa Rica and Panama, which included 34 interviews plus participant observation at 18 energy and infrastructure sites. Discussion of the findings explores Canada’s participation in selected extractivist projects, and offers an approach to analyzing transnational involvement through categories of Consumption, Investment, Promotion, and Provision. Given the relationship between these findings and the map-making process, the paper emphasizes the ability of radical cartography and graphic art projects to generate theoretical insight for academic research and to communicate findings to non-academic participants.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.019 | 0.012 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".