Left behind: emerging oil and gas producers in a warming world
Bibliographic record
Abstract
The push for decarbonization is dampening resource prospects in nations with undeveloped oil and gas. It is critical to reduce greenhouse gas (GHG) emissions from the petroleum sector, but there are equity issues related to requiring a shift away from oil and gas before development gains are made, especially in countries that have contributed very little to historical emissions. We review the prospects for five emerging producers to produce oil and gas at the lowest emissions intensity while achieving their economic and environmental goals. We find they lack the required capacity for stringent emissions management and to manage transition risks. The low-carbon pathway presents its own challenges with plans that lack national specificity and offer no substitute to the fiscal potential of the petroleum sector, and a lack of supportive technical assistance and finance. A just transition (JT) approach in these countries will not be about reskilling as they move away from a petroleum dependent economy, but instead about engaging with citizens to break the mould of petroleum-led development expectations and defining the new pathway for development. These countries will require support for transition planning that ensures that any oil and gas production minimizes GHG emissions, and limits the risk of economic lock-in, to invest in broad-based benefits and in a credible shift to a low-carbon economy. Inadequate international support risks leaving some countries behind, or to essential changes being contested in the transition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".