Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
These images are part of a larger project that explores multispecies relations in city space; how we humans can, and do, and must practice shifting our attention in acknowledgment of the others with whom we share land and our homes. For me, this shift in attention necessitates a kind of deeply reflective practice—deliberate and performative at first, but soon an embodied memory.Using macro photography, these pieces reflect one way of attending to a different scale and tempo of multispecies life. Here, I attune visually to the Catalpa leaf: a non-native tree transplanted to Toronto, for ornamental purposes. Importantly, attuning to the Catalpa leaf also shifts my conception of time and futurity. The present future is no longer solely anthropocentric but, rather, planthropocentric as well.We hold stories and memories in the tissues of our bodies, and these fleshy materials that compose us also create the patterns of our sensing and doing. Our tissues are sources of knowledge and of retention, and how they re-act tends to inform how we are able to relate. I believe this to be true of human-animals, and I believe it to be true of plants. If our bodies are capable of carrying so much experience and expression, what then might other multispecies bodies be capable of holding onto? What patterns or stories might other tissues retain or carry into the composition of the future?
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it