Bibliographic record
Abstract
Chestnut blight and mitten crabs from China, phylloxera from the eastern United States, musk rats from North America, gypsy moths from Eurasia, Canadian water weed and Colorado beetles. These are just some of the exotic biota, great and small, whose transatlantic histories the British animal ecologist, Charles Elton, related in his seminal text, The Ecology of Invasions by Animals and Plants (Elton, 2000 (orig. 1958)). Despite earlier studies of the transformation of New Zealand’s life forms and landscape through the transplantation of Eurasian non-natives (Clark, 1949; Guthrie-Smith, 1921), Elton is the first scholar with whom the subject of species transfer and biotic intermixing is readily associated. Elton’s book is remembered, not least, as a classic early warning of the deleterious consequences of certain exotics that launched the study of bio-invasion. Elton recalled that his interest in foreign flora and fauna was sparked during his boyhood in the bustling, cosmopolitan seaport of Liverpool before the First World War. Continuing the grand tradition of exotic introductions established by imperial Greeks and Romans (related here by Hughes (2003) and McNeill (2003))—if on a more modest and informal scale—sailors from around the world brought a wealth of faunal curiosities to the city. One of Elton’s favourite haunts was a shop in which these strange and wonderful living exotica were displayed (Elton, 1955). My own emerging preoccupation with what the botanical historian Edgar Anderson has called the ‘transported landscape’ (Anderson, 1967, p. 9) can perhaps also be traced to my boyhood in this area. Growing up in the days when nobody worried about children roaming the woods alone all day, I explored the same seashore and dunes blanketed in sand-stabilizing Corsican pine that Elton had tramped half a century earlier. More relevant to the contents of this special issue of Landscape Research, however, are the creatures I encountered on the Lancashire coast just north of Liverpool. Formby Point, now a National Trust nature reserve, is one of the last English strongholds of the native red squirrel, a national icon (thanks to Beatrice Potter’s tale of Squirrel Nutkin) whose status is as embattled as that of its Italian counterpart. These various essays span transported landscapes and their non-human denizens from the Classical world to Germany and South Africa in the 1930s. As my co-editor has pointed out, many introductions were uncontroversial and the acquisition of floral and faunal citizenship was an effortless process (see Kjaergaard’s account of clover’s benign conquest of Europe (Kjaergaard, 2003)).
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.111 | 0.066 |
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".