Nature Speaking of Nature to Nature : Animistic Communication Between the Veil of Reality and Fantasy
Bibliographic record
Abstract
Through the lense of Animism, the belief that every thing has a spirit and thus possesses its own agency, I am examining my engagement with materials in a subconscious collaboration that is mutually transformative. My own art practice I intuitively collaborate with natural magic and the energies and entities that occur through intrinsic interactions with the nature of all things. Humans who participate in communication with nature are in \ndialogue with nature within themselves and are thus part of nature. As radical feminist philosopher Susan Griffin says we are “Nature speaking of nature to nature”. \nIn this thesis I talk about my past work in sculptural costume making, poeticized archetypes and creating Living Cartoons. How this discipline bridged through my moving to Iceland from Canada and how I am exploring new sculptural disciplines with similar \nresults, surfacing Ambassadors from another realm. \nAll these elements come together in my work, when engaged with, to create a vortex of healing and initiation of change. Instead of a performative events, as I made in the past, I am making eventful vessels: containers of energy. When the viewer engages \nwith this object, or I with it during the creation process, the engagement becomes an event that activates the spirits who have collaborated in the making of it. In this event there is a \ncommunication that opens the in-between, a liminal space, where the potential for transformation is possible and the line between fantasy and reality is dissolved.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.049 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".