Bibliographic record
Abstract
The world is slowly transitioning away from fossil fuels. Much attention has been placed on technological breakthroughs needed for the green transition, such as longer-lasting batteries to extend the standard electric vehicle (EV) range, and on domestic and global policy challenges that accompany emissions reductions. Green technologies primarily rely upon critical strategic minerals (CSM). This article posits that just as the drive to control petroleum resources has shaped the twentieth century and the early decades of the twenty-first, so too will CSM shape the geopolitics of the rest of this century. In this article, I introduce a realist political economy framework to examine how reliance on critical inputs, whether fossil fuels or CSM, follows similar geostrategic parameters. I discuss how the fossil fuels transition offers opportunities for countries to develop new green industries through securing key inputs needed to build a green economy. CSM have both economic and security dimensions, and we can already see geopolitical rivalry taking place around the control of key sources of CSM in sub-Saharan Africa and Latin America, and by China around rare earths minerals.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".