Unsettled and unsettling tourism landscapes of Timor‐Leste
Bibliographic record
Abstract
This special issue explores how tourism in Timor-Leste operates as a dynamic arena for negotiating the nation's post-independence identity, development priorities, and nation-building processes.The papers in this collection illuminate the ways in which Timorese communities and stakeholders navigate competing visions of the nation's future, balancing tradition and modernity, while contending with the enduring legacies of conflict and colonisation.Moving beyond conventional framings of tourism as an economic driver, this issue foregrounds tourism's sociocultural and political dimensions.Tourism emerges here as a critical medium through which national, cultural, and historical identities are actively shaped, contested, and reimagined.The issue builds on discussions from the panel, Unsettled and Unsettling Tourism Landscapes of Timor-Leste, presented at the 2022 American Anthropological Association Annual Meeting in Seattle.Drawing on interdisciplinary perspectives and anthropological approaches (see Leite & Graburn, 2009;Nogués-Pedregal, 2019;Salazar & Graburn, 2014), the contributors explore tourism as a multifaceted field where local dynamics are interpreted and adapted, offering critical insights into the complex processes of cultural preservation, identity negotiation, and development in a post-conflict, post-colonial context.By adopting this broad lens, the issue offers an innovative framework for understanding tourism's role in Timor-Leste's post-independence era.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".