Dead-end pathways: Conceptualizing, assessing, avoiding
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
Despite rising climate urgency, decision-makers continue to support emission reduction options that appear promising on the face of it but hinder progress in practice. Whether through more efficient gasoline engines or waste heat recovery from fossil fuel combustion, many proposed solutions encourage partial emissions reductions without adequate consideration of whether they can build toward net zero systems of the future. As a result, it is essential that policy decisions are interrogated in terms of their alignment with net zero pathways (or lack thereof) and that decision-makers are both informed about and held to account for the compatibility of near-term choices with long-run system change. This study conceptualizes particularly problematic directions as ‘dead-end pathways’ and outlines a framework for identifying and avoiding them. The framework assesses pathways in relation to three dimensions: depth (how close they can come to virtually eliminating emissions in a stipulated system context), breadth (how widely they can be applied across the specified system), and timeliness (how rapidly they can be deployed). The study then applies this framework to three brief case studies drawn from road transportation, each of which fail on one of these dimensions.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it