The Creatures Collective: Manifestings
Bibliographic record
Abstract
This piece explores the work and entanglements of our research collective, formed in 2016. First, we collectively articulate the ethos and the motivations that inform the ways in which we labor to engage with complex, plural, multi-vocal experiences of extinction, “the Anthropocene,” and earth violence as they are felt and known across the diverse communities we represent. Then, drawing on more than three years of work across relations that tie us to Australia, Canada, Malaysian Borneo, the Philippines, and the United States of America, we share reflections on some of the vital relationships, methods, and “creatures” that animate our collaboration. This collection of “manifestings” aims to show how we work, very consciously, to foster more-than-human capacities for confronting the multi-scalar, cross-cosmological forms of violence that drive extinction and other forms of ecological harm in the world today.
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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.044 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".