Modes of Climate Engagement: Three Recent Case Studies of Climate Change-related Exhibitions
Bibliographic record
Abstract
The challenges of how to connect people to the seemingly abstract concept of climate change has been explored by countless researchers who aim to help people understand the impact of emissions on rising temperatures. Climate change-themed exhibitions offer new pathways for connection with difficult-to-grasp climatological concepts; these methods are similar to the ways in which Lauren Berlant claims art activism “interferes with the feedback loop whose continuity is at the core of whatever normativity has found traction.”1 This review of three such exhibitions—one in-person, one online, and one hybrid—explores how new forms of meaning-making can emerge out of these public proposals for what is, essentially, a greater engagement with the terms of climate change in the here and now. These exhibitions share questions of social responsibility by involving forms of new media and piquing the curiosity of visitors, offering rich case studies with which to examine how mediation operates on multiple levels, and potentially broadening public engagement with climate change.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".