Landscapes of Recarbonization: Carbon Neutrality, Settler Colonialism, and Cumulative Environmental Effects in the Peace River Region, Canada
Bibliographic record
Abstract
Contemporary discourses of net-zero decarbonization (also referred to as carbon neutrality) routinely overlook the landscape transformations required to offset carbon emissions. Conventional analyses also often fail to engage with decarbonization as an inherently spatial process, embedded in landscapes in which the biophysical, socionatural, and political economic dimensions of energy intersect. This creates a conceptual pitfall: the potential to misread and depoliticize strategies of putative decarbonization that might not, in fact, be carbon neutral, particularly when the cumulative effects of broader landscape transformations are considered. To illustrate this pitfall, our analysis queries net-zero decarbonization strategies that arise alongside—and often as a result of—simultaneous investments in fossil fuel production, a process we term recarbonization. We posit recarbonization as a variegated sociospatial phenomenon that materializes through the site-specific interplay between capitalist social relations and biophysical processes. In making this claim, we seek to bridge political economy with concepts of materiality and relationality that, we suggest, enable deeper theoretical engagement with multifaceted landscape transformations entailed by processes of energy transition. Drawing on a case study of the Peace River region in the western Canadian provinces of Alberta and British Columbia, this article exposes the cumulative environmental effects and ongoing forms of colonial violence of some net-zero decarbonization agendas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Science and technology studies | 0.025 | 0.023 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".