Bibliographic record
Abstract
We write about the poetics of kinship with birds, trees, stones, and places as an act of resistance to neo-literal, neo-liberal destruction of refuge for non-human beings. Through research in which we situate ourselves in relation to the more-than-human, we take up kin as a verb. We offer experiences of kinning—that is, being present with that which is alive, has agency, and gives voice—as an invitation to readers to open themselves to listen in life and in research. We write in dialogue, through letters to each other, and we write poetically. With poetry’s attention to metaphor, embodiment, and vision, it is the natural language for describing the experience of kinning. Inquiring poetically helps us regain a communicative being-in-relation with wild, more-than-human others at a time of ecological distress, and to seek to better appreciate mystery and understandings that exceed human forms of knowing. Through this paper, we theorise from within our understandings and experiences about poetically kinning with the more-than-human.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".