Feminist Infrastructure for Better Weathering
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
Big infrastructure responses to climate change seek to protect the heteropatriarchal capitalist status quo. In contrast, this article develops a theory and method of practice-led research to facilitate better weathering. In so doing the article contends that a transformative feminist response to climate change needs alternative, collective, feminist infrastructures. The feminist specificity of the infrastructure proposed here emerges through its proximity to the concept ‘weathering'. As a feminist figuration, weathering attunes us to human embodiment and difference in a time of climate change, where ‘weather' is not only meteorological, but the total atmospheres that bodies are made to bear. An infrastructure for better weathering thus centres opportunities to acknowledge and account for embodied difference and the differential effects of weather as a specifically feminist design feature. Better weathering is not neoliberal resilience, but rather attention to and redistribution of low-stakes vulnerability as an infrastructural politics. The article proceeds in two parts. We theorise a feminist infrastructure. We then pilot the infrastructure in a series of practice-led research activities. We argue these new infrastructures facilitate low-stakes vulnerability between strangers and so enable better weathering.
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 | 0.002 | 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