Finding Beauty in the Dragon: The Role of Dragonflies in Recreation and Tourism
Bibliographic record
Abstract
In some Asian countries such as China and in Japan, Odonota (dragonflies, damselflies) have a long history of being involved in recreation and leisure activities. In contemporary Japan, dragonfly enthusiasts, much like birders elsewhere, pride themselves on recognizing many different types of Odonata. In fact, numerous symposia, festivals, and sanctuaries provide Japanese dragonfly enthusiasts with the opportunity to practice and perfect their skills (Primack et al., 2000). Dragonfly gatherings (e.g., counts, educational outings) in North America and Europe are also increasing in popularity. Facilitating the growth of these recreation activities, but more specifically the viewing of dragonflies, are the availability of books and field guides (Corbet, 1999; DuBois, 2005; Dunkle, 2000; Mead, 2003; Nikula et al., 2002), associations (e.g., Dragonfly Society of the Americas, Worldwide Dragonfly Association), and websites (e.g., Digital Dragonflies). This article examines discussion surrounding insect-human relationships while highlighting the contribution of one particular insect order – Odonata (Mitchell & Lasswell 2005; Moore 1997), and the role of this flagship species in socio-cultural norms (Samways 2005) in recreational and tourism activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".