Post-growth and the lack of diversity in the scenario framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scenarios and pathways, as defined in the SSP-RCP framework, are central to recent climate research and the latest IPCC report. Shared Socioeconomic Pathways (SSPs) offer a small set of alternative futures through qualitative narratives and quantitative projections. A key use of SSP-based scenarios is mitigation analysis, presenting decision-makers with a seemingly neutral set of policy options. However, all SSPs assume continuous global economic growth (GEGA) through 2100, effectively narrowing the solution space and embedding value-laden assumptions that challenge the IPCC’s claim to policy neutrality. Post-growth scholars contest GEGA, but post-growth mitigation scenarios have yet to be fully integrated into this scenario framework. From a philosophy of value-laden science perspective, I argue that this integration is necessary. I propose two approaches to do so, demonstrating how inclusion of post-growth scenarios aligns with a diversity criterion — ultimately enhancing the framework’s objectivity and strengthening the IPCC’s policy neutrality.
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.
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 | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it