Bibliographic record
Abstract
Abstract In popular conservation discourse, Rhododendron ponticum is portrayed as an alien invader let loose on the British countryside by misguided gardeners. In Scotland, eradication campaigns tend to be favored over more pragmatic approaches to management, even though the methods employed can be destructive and long-term success is often limited. Building on recent work critiquing categorical approaches to invasive species management, we argue that such campaigns obscure not only the underlying conditions but also the ongoing production of plant invasiveness. We focus in particular on the way perceptual processes shape and are shaped by plant “invasions” over time. Noting that the majority of plant invasions worldwide are initiated by the horticultural trade, and that visual appearance is a major factor in the selection of plants for trade, we present a framework for critically analyzing the visual conditions of horticulturally led invasion ecologies. Working from the perspective of a more-than-human, materialist media ecology, we cast rhododendrons as entities that modulate light, or “photomedia.” Our analysis explores how their invasiveness is materially produced via the cultural and socioeconomic as well as vegetal relations in which they are entangled. The site of our analysis is an abandoned country estate in western Scotland that has recently undergone R. ponticum removal. By examining the production of visual effects by rhododendrons, cameras, and other media employed there, we identify relations to land that, far from being limited to the period of R. ponticum’s “escape” into the Scottish countryside, continue in present-day projects of eradication. This yields critical visual strategies for a gentler, more experimental re-mediation of R. ponticum and invaded landscapes in general.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".