“The War in the Woods”: Post-Fordist Restructuring, Globalization, and the Contested Remapping of British Columbia's Forest Economy
Bibliographic record
Abstract
Resource peripheries that are geographically remote from “core economies” are also peripheral to contemporary theorizing in economic geography, and requires higher profile within economic geography's research agenda. The restructuring qua remapping of resource peripheries is collectively shaped by institutional forces unleashed by post-Fordism and globalization that are fundamentally different from the restructuring of cores. As industrial regions, resource peripheries must negotiate the imperatives of flexibility and neoliberalism from vulnerable, dependent positions on geographic margins. For many resource peripheries, neoliberalism has been perversely associated with trade protectionism. As resource regions, the restructuring of resource peripheries has been further complicated by resource-cycle dynamics and radically new social attitudes toward the exploitation of resources that have helped spawn the politics of environmentalism and aboriginalism. Trade, environmental, and aboriginal politics have clashed around the world to contest vested industrial interests and remap resource peripheries in terms of their value systems. British Columbia's forest economy illustrates this contested remapping. For two decades, the powerful forces of neoliberalism, environmentalism, and aboriginalism have institutionalized a “war in the woods” of British Columbia that is sustained by shared criticism of provincial policy and disagreement over how remapping should proceed. The authority of the provincial government, which controls British Columbia's forests, has been undermined, but it remains vital to socially acceptable remapping. Meanwhile, the enduring war in the woods testifies that geography matters on the periphery.
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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 | 0.002 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".