The emerging hypercarbon reality, technological and post-carbon utopias, and social innovation to low-carbon societies
Bibliographic record
Abstract
Emphasis has shifted in climate change politics from fear to dreams and opportunities. This article demonstrates that many social science analyses of anthropogenic climate change are characterized by utopian presumptions, including technological mastery of nature, and that key concepts such as post-carbon society, decarbonization, low-carbon transitions, ecological direction of travel, and ecological modernization have not been defined in terms of the absolute amount of emissions appropriate for anthropogenic global warming. It shows that time-cost discounting is erroneous. These misleading conceptions give false positives for improvement and sustain wishful thinking in societies that have locked themselves into carbon-based infrastructures where default options are fossil fuels leading to an emerging path-dependent hypercarbon world. The article explains how those concepts can be reconceptualized to increase validity and also suggests accurate concepts like time-cost exacerbation, low-carbon and decarbonization transition searches, and ecological modernization niches. By comparing longue durée emitting societies, it documents the superiority of (1) social democracy over neoliberalism in transitioning to low-carbon economies while enhancing democracy, equity, and prosperity, and (2) multitasking of international mitigation commitments with local mitigation, adaptation, and resilience. The article seeks to stimulate research into learning from better performing societies to innovate transitions of institutions and culture to robustly defined low-carbon economies.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.055 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".