Bibliographic record
Abstract
Academic interest in global energy politics increased drastically in the 1970s when the Organization of Petroleum Exporting Countries (OPEC) cut oil production to punish the West, leading to escalating gasoline prices.The crisis highlighted that energy is inextricably linked to global politics, sparking the creation of a new disciplinary field: international political economy (IPE) (Hancock & Vivoda, 2014, p. 6).Scholars escalated their research.However, when the price of oil declined, so did publications, particularly in mainstream international relations (IR) journals; they remained stagnant for decades (Hughes & Lipscy, 2013).The paucity of energy politics publications became more obvious and problematic with dramatic changes in the global energy landscape including the rise of China and its massive consumption and production and Russia playing "pipeline politics;" major increases in renewable energy (RE) production and related political actors; oil and gas finds in Africa and Asia; hydraulic fracturing ("fracking") technology that led to the US becoming a net exporter in 2020, for the first time since at least 1949; new regional and global energy governance structures (e.g. the EU's Energy Union); new energy institutions, such as the International Renewable Energy Agency (IRENA); increasing certainty about climate change science and the 2015 Paris Agreement; the Fukushima disaster that changed views and policies about nuclear energy.This Special Issue's focus stems from four rarely linked trends.First, academic interest in regions and comparative regionalism, in which scholars rigorously compare formal and informal institutions, players, and processes for creating and maintaining regions, and issues between regions (Acharya, 2012;Balsiger & VanDeveer, 2012; Börzel & Risse, 2016;De Lombaerde et al., 2010;Hameiri, 2013).Second, a growing group of IR scholars turning their attention to energy.Third, IR scholars increasingly using lenses other than the traditional security one.Finally, a trend toward analyzing informal governance and non-state actors, along with formal institutions and state-led efforts.The scarcity of literature on energy regions is not just an "academic" problem.Understanding how regionalisms-players, processes, institutions, and organizations-intersect with energy is directly linked to domestic and international energy policies and outcomes.For example, regional energy infrastructure meant to improve standards of living in lower income states sometimes flourishes and other times fails disastrously.They sometimes benefit only elites, fueling corruption.Development goals may go unreached, and aid wasted, due to poor design and a weak or inaccurate understanding of regional dynamics.Energy projects can create negative externalities, in which energy production in one state negatively affects neighboring states.Exploring energy regionalisms promises to feed into both pertinent academic debates and broader international relations and domestic challenges.At the empirical level, starting in the late 1980s, there's been a "reinvigoration" of regional cooperation, especially in the global South (Kacowicz, 2018, p. 61) but in all world regions and across numerous issue areas (Schneider, 2017, figure 1, p. 230).This phenomenon is documented
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.080 | 0.034 |
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".