Bibliographic record
Abstract
Abstract This book explores how and why controversies over liquid biofuels (bioethanol and biodiesel) and hydraulic fracturing (“fracking”) unfolded in surprisingly similar ways in the Global North and South. In the early 2000s the search was on for fuels that would reduce greenhouse gas emissions, spur economic development in rural regions, and diversify national energy supplies. Biofuels and fracking took center stage as promising commodities and technologies. But controversy quickly erupted. Global enthusiasm for these fuels and the widespread projections for their production around the world collided with local politics. Rural and remote places, such as coastal east Africa and Canada’s Yukon territory, became hotbeds of contention in these new energy politics. Opponents of biofuels in Kenya and of fracking in the Yukon activated specific identities, embraced scale shifts across transnational networks, brokered relationships between disparate communities and interests, and engaged in contentious performances with symbolic resonance. To explain these convergent dynamics of contention and resistance, the book argues that the emergence of grievances and the mechanisms of mobilization that are used to resist new fuel technologies depend less on the type of energy developed than on intersecting elements of the political economy of energy—specifically finance, ownership, and trade relations. Taken together, the intersecting elements of the political economy of energy shape patterns of resistance in new energy frontiers.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 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".