Bibliographic record
Abstract
“Once you have done your homework you realize we need new politics, we need new economics … We need a whole new way of thinking.” Greta Thunberg, speech at EESC event “Civil Society for rEUnaissance” There were fortunes to be made in coal and then oil, and now gas too. More than just fortunes are involved; modern economies depend on these fuels, and states only function if fuels are available to keep modern life going. Access to fuel has been essential to the security of modern states and their inhabitants. The rivalries of states and corporations, the struggles for dominance and control, the political arguments about who has access to what where matters. In other words, geopolitics are indivisible from fossil fuels in the modern world. Other resources have been involved in all sorts of conflict and imperial plunder through history (LeBillon 2012), but oil has pride of place in recent decades. A sustainable future now requires dismantling these systems and replacing both the technologies and their social and economic arrangements with ones fit for a small vulnerable biosphere. No longer can assumptions of a big world as a stage for geopolitics operate if the long-term future of humanity is to be secured. Numerous peoples have long paid a high price for the struggles for power and space set in motion by European colonization and the expansion of capitalism through the Earth system (Grove 2019). Now even those who have benefited most from these colonial arrangements and their subsequent evolution into the global economy are beginning to feel the impacts of sea-level rise and climate disruption. The large oil companies are truly global companies with holdings and infrastructure in many countries. Crucially in many places they held the rights to exploit petroleum and their wealth was tied to the valuations of these reserves. This is often still the case and stock values are linked directly to gaining access to what lies deep underground. States have struggled to exploit these resources and enrich themselves in the process too. The case of the Gulf States, sheikdoms sitting on oil fields, emphasizes the point that there are vast fortunes to be made. But fuel resources are unevenly spread around the globe, and while some states and corporations have gained enormous wealth others have had economic disruptions because of their dependence on fuel from abroad.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.070 |
| Scholarly communication | 0.017 | 0.031 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".