Bibliographic record
Abstract
This essay positions John Ruskin’s 1884 lecture ‘The Storm-Cloud of the Nineteenth-Century’ and its accompanying Annotations in relation to experimental methods in co-writing and an implicit challenge to prevailing understandings of the individual. Ruskin’s essay has been much discussed for anticipating the climate crisis and staging the struggle to find terms for concepts that, as Jesse Oak Taylor argues, have not yet emerged. I turn to another related dimension of Ruskin’s essay: its practice of what I call ‘co-writing’ capaciously understood (Ruskin writing with others, with himself, with the political and social events of the day, and with the clouds). Unlike ‘the future meteorologists’ to whom he refers, Ruskin does not have a community on all points of the globe to synchronise observational results and arrive at conclusions. He instead multiplies his voice and in the process illustrates how no voice is one voice but rather is interwoven with illimitable others and no one, truly, works alone. This essay further argues that reconfigurations of the individual via co-writing and other experimental methods – including, for example, the EVENT conference hubs and platform for online annotation – may offer more robust avenues for climate action.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".