A garden of unplanted species: Andrew Dadson's countervisuality of weeds
Bibliographic record
Abstract
Weeds are ever-present within our natural and urban environments: growing through the cracks in the pavement, accompanying our gardens, and carpeting human-induced dereliction. Humans often, socially and linguistically, refer to them as a nuisance, but what if we instead viewed them as resilient, dynamic contributors to the sustainability of our planet, especially as we endure the increasingly severe environmental crisis? Negating these discriminating modes of visuality, this thesis argues that Vancouver artist Andrew Dadson’s 2019 series of photographs is a countervisuality through strategies of reportage, gentle earth interventions and high-resolution photography. With reference to the work of scholars working to decenter the human while raising the agentic capacities of nonhuman entities, including Donna Haraway, Anna Lowenhaupt Tsing, N. Katherine Hayles, Michael Marder, and Michael Pollan, Dadson’s work argues for the resuscitation of weeds into a renewed reality and legitimacy. His photographs offer a liminal positionality between documentary and artifice, reminiscent of Jeff Wall’s contribution to Vancouver photoconceptualism, while his enactment of painting plants – corporeally suffusing the landscape – echoes the gentle gestures of land artists Richard Long and Andy Goldsworthy. By using advanced photographic technology that captures weeds in hyper-resolution and definition, I argue with Joanna Zylinska’s notion of nonhuman photography that Dadson’s works invite the spectator to imagine walking the horizontal ground, brushing against the soft, spindly fibers, and breathing the same oxygen that maintains weed life
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".