On the care of cottonwood: tending and attending to our sentinel trees
Bibliographic record
Abstract
This is a project devoted to a tree. The tree is the Plains cottonwood, known for its superlative growth rate, size, and longevity in the Great Plains. Well attuned to local growing conditions, cottonwood are among the tree species that define Winnipeg, a city of 750,000 people located in Manitoba, Canada. I call these trees sentinels because those that reach maturity witness much change in their 200+ year lifespan.\n\nWinnipeg’s urban cottonwood population is composed of mature declining trees; a small number of planted trees; and self-seeded trees growing in leftover land, unlikely to survive to middle age. The mature declining class is the most ecologically, spatially, and, I argue, culturally significant of the population. As things are, no near-future population of mature cottonwood will be as numerous or widespread. Shifts in the regional hydrological system and in patterns of human settlement and interaction result in fewer opportunities for natural cottonwood propagation. This, coupled with their largeness, perceived ill-suitedness for urban spaces and enduring image as a seedy, short-lived nuisance tree, has led to chronic underplanting. \n\nWhat, then, I see as a design response is clear: plant more cottonwood. But rather than simply plant trees, I propose establishing distinct cottonwood configurations that we can tend and attend to over time as we do our current sentinels and in new ways that celebrate the tree, our shared histories, and the processes critical to a cottonwood’s lifecycle, being, and meaning.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".