Bibliographic record
Abstract
Exploring air, airborne phenomena, and elemental representation, this book dissects the materiality of air, which comes to the fore ever more vigorously given the ongoing environmental and health crises. Understanding air’s materiality is essential to outlining clear solutions to the current challenges and to generating new meanings of what constitutes an environmentally safe and healthy future. The dual nature of air makes it a rich field for metaphor and a potent subject to think with: as space that contains and engages with other elements, particles, and beings; and as matter that moves, envelopes, and penetrates objects, spaces, and time. Each chapter offers new perspectives on air’s material qualities, treating air as a literal and figurative element that provides an important lens on climate change, toxicity, pollution, capitalism, violence, and transmission, among other issues. The volume also highlights future directions for engaging with the all-important medium of air. This edited collection responds to the growing scientific and scholarly explorations of elements and the elemental, as well as the complex environmental, sociopolitical, economic, and cultural issues that emerge through these elements. Bringing together experts from the environmental humanities, health humanities, cultural studies, literary studies, art, and history, the chapters consider the intricate relationships between humans, more-than-humans, and the environment more broadly.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".