The Geopolitics of Climate Knowledge Mobilization
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
Climate change and sustainability science have become more international in scope and transdisciplinary in nature, in response to growing expectations that scientific knowledge directly informs collective action and transformation. In this article, we move past idealized models of the science–policy interface to examine the social processes and geopolitical dynamics of knowledge mobilization. We argue that sociotechnical imaginaries of transdisciplinary research, deployed in parallel to “universal” regimes of evidence-based decision-making from the global North, conceal how international collaborations of scientists and societal actors actually experience knowledge mobilization, its systemic barriers, and its paths to policy action. Through ethnographic study of a transdisciplinary research program in the Americas, coupled with in-depth analysis of Colombia, we reveal divergences in how participants envision and experience knowledge mobilization and identify persistent disparities that diminish the capacity of researchers to influence decision-making and fit climate knowledge within broader neoliberal development paradigms. Results of the study point to a plurality of science–policy interface(s), each shaped by national sociotechnical imaginaries, development priorities, and local social orders. We conclude that a geopolitical approach to transdisciplinary science is necessary to understand how climate and sustainability knowledge circulates unevenly in a world marked by persistent inequality and dominance.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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