Bibliographic record
Abstract
How organized resistance to new fossil fuel infrastructure became a political force and how this might affect the transition to renewable energy. Organized resistance to new fossil fuel infrastructure, particularly conflicts over pipelines, has become a formidable political force in North America. In this book, George Hoberg examines whether such place-based environmental movements are effective ways of promoting climate action, if they might inadvertently feed resistance to the development of renewable energy infrastructure, and what other, more innovative processes of decision-making would encourage the acceptance of clean energy systems. Focusing on a series of conflicts over new oil sands pipelines, Hoberg investigates activists' strategy of blocking fossil fuel infrastructure, often in alliance with Indigenous groups, and examines the political and environmental outcomes of these actions. After discussing the oil sands policy regime and the relevant political institutions in Canada and the United States, Hoberg analyzes in detail four anti-pipeline campaigns, examining the controversies over the Keystone XL, the most well-known of these movements and the first one to use infrastructure resistance as a core strategy; the Northern Gateway pipeline; the Trans Mountain pipeline; and the Energy East pipeline. He then considers the “resistance dilemma”: the potential of place-based activism to threaten the much-needed transition to renewable energy. He examines several episodes of resistance to clean energy infrastructure in eastern Canada and the United States. Finally, Hoberg describes some innovative processes of energy decision-making, including strategic environment assessment, and cumulative impact assessment, looking at cases in British Columbia and Lower Alberta.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".