Conflicted tourism : heritage narratives, sectarian schism, and economic growth in Northern Ireland.
Bibliographic record
Abstract
This thesis examines tourism as a politically charged facet of the economic process in Northern Ireland. While violence has abated in the region, sectarian conflict continues to affect Northern Irish society. Tourism has helped develop the economy by opening the market to visitors through the marketing of the region as unique and different. As conflict in the region is ongoing, the rise of tourism as a viable economic strategy raises the question: how does the Northern Irish tourist industry reconcile the past and ongoing conflict in order to present the region as a desirable tourist destination? The answer lies in the creation and appropriation of conflict sites. Conflict sites involve heritage. By focusing on these types of tourist attractions, attention is brought to the hidden – and continual – process of historical (re)formulation. The analytical categories of local-folk and official are instrumental in examining this process. They capture differing perspectives. The local-folk and official perspectives are not completely distinct. Instead they are intertwined and influence one another. They also vary across time and space. The concept of conflict tourism helps generate and address specific questions about such variation. How did the tourism industry develop within the socio-economic and political spheres? How has it affected these spheres? Most specifically, why and how have sites connected with the events of the Troubles been appropriated and reimagined as tourist spaces? Answering such questions requires attention to the socio-political framework of the Northern Irish economy, the creation and marketing of the tourism industry, the impact conflict has upon tourist activities, and the impact tourism has upon conflict.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.009 |
| 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".