Growth‐inducing infrastructure represents transformative yet ignored keystone environmental decisions
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
Abstract As the defining force of the Anthropocene, human enterprise is reshaping Earth's surface and climate. As part of that process, growth‐inducing infrastructure, such as electrical transmission lines, export facilities, and roads, presents nonincremental changes in where and how natural resources are exploited. These projects open intact areas, induce or intensify industrial development, and accelerate carbon emissions. The direct impacts of large‐scale infrastructure are widely acknowledged and policy and legislation exists to account for them in environmental decisions. Yet, decision makers often ignore the secondary, growth‐induced effects, even though they can outweigh the impacts of the initial development. Given the extensive area and magnitude of such impacts, we argue that regulatory or funding approvals for growth‐inducing infrastructure represent keystone decisions. Credible approval processes require the consideration of the full range of impacts resulting from the ensuing growth. This will necessitate a shift in assessment thinking, from the traditional focus on the immediate project footprint to one that recognizes the sustainability implications of approving infrastructure that will transform the trajectory of development at regional and national scales. We identify the characteristics of growth‐inducing infrastructure and provide an overview of methods and policy that can facilitate a deliberate assessment of these keystone decisions.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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