Anywhere but here: Experiences of islandness in Pearl River Delta island tourism
Bibliographic record
Abstract
This study considers the phenomenology of ‘islandness’ by analysing the experiences of tourists, islanders, and migrant tourism workers on two Chinese islands in the South China Sea. Although we begin by presuming place to be a phenomenological concept centring on ‘being-in-the-world’, we find that people’s experiences both on and off the islands of Dong’ao and Wailingding engender a desire to ‘be-in-many-worlds’ at once. Findings drawn from three months of ethnographic fieldwork suggest that while tourists privilege ‘being-at-the-seaside’, long-term residents prioritize being both ‘on’ and ‘off’ the island. Meanwhile, migrant tourism workers’ sense of islandness emerges from ‘being-at-theseaside’ and ‘being-on-the-island’. In all cases, we find that islands challenge people’s desires to dwell in just one specific place to which they have an attachment. We argue that this liminal place attachment arises partly because the physical geography of islands, being surrounded by the sea, facilitates movement and may prompt a longing for elsewhere. Our findings have consequences for the phenomenology of place, which assumes that people have an innate desire to be somewhere. Yet thinking through and from islands shows that people equally wish to be somewhere else, too. The manifold human experiences of islandness underscore the need for a more relational phenomenology of place based not just on ‘being-in-the-world’, but rather ‘in-many-worlds’ at once.
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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 | 0.002 |
| 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 | 0.003 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".