Mobilizing smart grid experiments: Policy mobilities and urban energy governance
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
Cities across the US have been looking to urban experiments as a way to demonstrate potential pathways for carbon control, economic development, and resilience. On their own, these experiments are often small in scale and highly localized, embodying a piecemeal approach to urban development and climate governance. In this paper, I examine the relationship between urban experimentation and policy mobilities to understand how these projects have broader significance for climate governance and urban development. Drawing together empirical data from a multisited case study of smart grid experiments in Austin, Texas; Boulder, Colorado; and Chicago, Illinois, I show how governmental rationalities are mobilized, mutated, and transmitted in the processes of urban learning, extrospection, and consultation. While the imperative of cities to respond to climate change is ever more central to urban politics and governance, I find that the logics of experimentation are tied to specific governmental rationalities and norms of conduct that embed limited notions of citizen involvement and engagement in policy. The paper outlines how three elements of an Austin smart grid model—users as test-bed, test-bed as platform, and test-bed as epistemology—reinforce these logics and rationalities. The implications for urban climate and energy governance are outlined stressing three synergies between urban experiments and policy mobilities approaches.
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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 | 0.001 |
| 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