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 communication is seemingly stuck in a double bind. The problem of global warming requires inherently trans-scalar modes of engagement, encompassing times and spaces that exceed local frames of experience and meaning. Climate media must therefore negotiate representational extremes that risk overwhelming their audience with the immensity of the problem or rendering it falsely manageable at a local scale. The task of visualizing climate is thus often torn between scales germane to the problem and scales germane to individuals. In this paper I examine how this scalar divide has been negotiated visually, focusing in particular on Ed Hawkins’ 2016 viral climate spiral. To many, the graphic represents a promising union of political and scientific communication in the public sphere. However, formal analysis of the gif’s reception suggest that the spiral was also a site of anxiety and negative emotion for many viewers. I take these conflicting interpretations as cause to rethink current assumptions about best practices and desirable outcomes for scalar mediations of climate and their capacities to mobilize a wide range of reactions and interpretations—some more legibly political and some more complicatedly affective, yet all nevertheless integral to the work of building a holistic response to the climate crisis.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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