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Record W4230940150 · doi:10.4324/9780203340332-18

The paradox of a tourist centre: Hong Kong as a site of play and a place of fear

2004· book-chapter· en· W4230940150 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsnot available
Fundersnot available
KeywordsTourismAdvertisingMedia studiesHistoryGeographySociologyBusinessArchaeology

Abstract

fetched live from OpenAlex

Economic globalization and advances in transport and communication technologies are central to increased travel. Travel by business people, tourists, and diasporas has stimulated the mobility of capital, goods, services, people, knowledge, and disease from one location to another (Urry 1995: 173; chapter 18 in this volume). Until the terrorist attacks of 11 September 2001, international travel for both play and work had taken off in an upward direction. This event adversely affected passenger numbers and miles travelled on a global scale. The SARS outbreak in spring 2003 did not have the same global impact but did severely affect travel to and from Hong Kong, some other Asian cities, and Toronto. Largely in seeking to capture these mobile flows, cities, regions, and nation-states compete to imagine and sell their historical image and locational advantages to international investors and tourists in an ever-tightening global economy (Kearns and Philo 1993; Short and Kim 1999; Hall 2000). Within the tourist industry, diverse destinations are constructed to capture the flow of tourists and to direct them to specific sites of play (Judd and Fainstein 1999). These destinations often involve the construction of various forms of ‘adventure’ and/or ‘otherness’ that can ‘spice-up’ the experience of specific tourist play (Hooks 1992). This chapter specifically examines Hong Kong before and after the 1997 transition from British colony to Special Administrative Region (SAR) of the People’s Republic of China, and the changing nature of its East-West play within the global tourist economy.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.726
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.250
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations6
Published2004
Admission routes1
Has abstractyes

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