Ecologies of Embodiment: Video Essays I
Bibliographic record
Abstract
Csenge Kolozsvari, "Bodylandscapes I." (10:58). A proposition for remembering the ecological ways of belonging, a feeling into other ways of knowing, connecting into the vastness that surrounds us and moves across us, becoming-environment once again. // Anja Plonka, Marko Stefanovic, and Rasmus Nordholt-Frieling, "Breathing Gaia: Searching for Kinship Around Walensee" (8:28). The video essay creates a speculative-utopian body and existence of human and non-human. The body as an archive of traumatic inscriptions practices transformation as a being in resonance with Gaia. // Jessica Marion Barr, Jenn Cole, and LA Alfonso, "Our Bodies, These Lands: Practising Reciprocity" (6:03). As artist-researchers with embodied practices and relationships with lands and waters, we explore a unique part of Michi Saagig Nishnaabeg territory wherein “rockmills” or “kettles” offer spaces for our human selves to be held and surrounded by massive ancient rock beings. // Alessandro Guglielmo, "Wisdom and Trouble: Notes on Blood, Care, and Death in Multispecies Settings" (9:30). In this video essay, I employ my emplacement as a vegetarian anthropologist witnessing the killing of a non-human being to produce an understanding of more-than-human ecologies. I reflect on narratives of death, and the trouble of care and killing in multispecies settings.
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 | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".