'The Dragon Run' : a travel memoir of Bhutan with critical commentary examining representation of the self in modern travel writing
Bibliographic record
Abstract
The creative component of this dissertation is excerpts from 'The Dragon Run', a travel memoir recounting the author’s experiences living in and running across Bhutan (2006-2008). Aligning itself with the accounts of contemplative travel writers from the West who have spent extended periods in the Himalayan Kingdom, the memoir is as revealing psychologically and temperamentally of the narrator as it is descriptive of the nature and culture of the host country. However, it differs from these accounts in that a distinction is made between the naive newcomer to the country and the more discerning sojourner. It also contrasts thematically in that the narrator’s reflections engage with themes associated with the Kingdom’s drive to modernise before its first parliamentary election: Gross National Happiness, the ‘Last Shangri-La,’ Buddhist ethics, the value of wilderness and the virtue of raising funds to send village children to school. The critical commentary that follows the creative element examines self-revelation in contemporary travel writing, the argument being that a travel book has greater appeal when an interior voyage runs parallel to the outer one. Part I argues that the fictional techniques travel writers commandeer to represent their journeying selves, such as the articulation of thoughts, mingling of dramatic scenes with personal reflection and tracing of a path of learning, endow their protagonists with psychological depth. Part II finds that the ways in which authors have their travelling selves respond to wilderness give insight into their personalities: their spiritual connection with nature, their sadness at its destruction, the solace they draw from close contact. Part III considers the legacy of Orientalism in modern travel writing and argues that balanced treatment of people belonging to other cultures and greater understanding of the self depend on the sensitivity of the traveller to his or her own culture. Provided that the travel writer does not mythologise too freely, self-disclosure enriches the book through arousing readers’ interest as much in the traveller as his or her travels. The narrative strategies that travel writers use to represent the inner lives of their voyaging personas manufacture the interior journey. Study of them informs the decisions the author has made in writing 'The Dragon Run'.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.021 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".