The future of renewable energy systems—a long and winding transition pathway?
Bibliographic record
Abstract
Many sources of renewable energy have been identified as replacements for fossil fuels. But what exactly is a renewable energy source? Of the numerous attempts to provide a definitive answer to that question none are wholly satisfactory but, generally, it appears that a renewable source is any that is not carbon based, except for biomass, and its supply can be sustained naturally or by human action, i.e., tree-planting. In the ‘utopian’, or ‘unconstrained’, vision it is claimed that the use of renewables can solve, not just manage, all the problems associated with anthropogenic climate change. Indeed, the United Nations asserts that renewables are safer, cheaper, healthier and their adoption could create millions of new jobs and, by 2050, have a huge positive financial impact on the global economy. With such appealing virtues it is surprising that renewables provide less than a third of the world’s generated electricity and far less of the overall global primary energy consumption, despite significant increases in recent years. Is this because the claims are overstated or is the impatience, and sometimes intolerance, of the protagonists of renewable energy transitions detrimental to more general acceptance? If the laudable aim of the eradication of global poverty, largely through sustainable development, is to be achieved, and if renewable energy sources can play indispensable roles in its realization, what practical steps need to be taken towards universal credibility and access? What tools do policymakers have at their disposal when planning the way ahead for renewables? Would more pragmatic, albeit imperfect, approaches to determining the nature of future energy mixes based on national usage patterns be valuable rather than endlessly debating the efficacy of climate models. These matters are discussed in this chapter.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.013 | 0.029 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".