The Serpent (2021): monstrous tourism, a serial killer, and the Hippie Trail
Bibliographic record
Abstract
The Netflix/BBC eight-part limited true crime series The Serpent (2021) provides a commentary on the impact of the tourist industry in South-East Asia in the 1970s. The series portrays the story of French serial killer Charles Sobhraj (played by Tahar Rahim)—a psychopathic international con artist of Vietnamese-Indian descent—who regularly targeted Western travellers, especially the long-term wanderers of the legendary “Hippie Trail” (or the “Overland”), running between eastern Europe and Asia. The series, which was filmed on location in Thailand—in Bangkok and the Thai town of Hua Hin—is set in a range of travel destinations along the route of the Hippie Trail, as the narrative follows the many crimes of Sobhraj. Cities such as Kathmandu, Goa, Varanasi, Hong Kong, and Kabul are featured on the show. The series is loosely based upon Australian writers Richard Neville and Julie Clarke’s true crime biography The Life and Crimes of Charles Sobhraj (1979). Another true crime text by Thomas Thompson called Serpentine: Charles Sobhraj’s Reign of Terror from Europe to South Asia (also published in 1979) is a second reference. The show portrays the disappearance and murders of many young victims at the hands of Sobhraj. Certainly, Sobhraj is represented as a monstrous figure, but what about the business of tourism itself? Arguably, in its reflective examination of twentieth-century travel, the series also poses the hedonism of tourism as monstrous. Here, attention is drawn to Western privilege and a neo-orientalist gaze that presented Asia as an exotic playground for its visitors. The television series focuses on Sobhraj, his French-Canadian girlfriend Marie-Andrée Leclerc (played by Jenna Coleman), and the glamourous life they lead in Bangkok.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 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 teacher head, 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".