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Record W778010584 · doi:10.24006/jilt.2004.2.1.5

Leisure Port Development in the Incheon Area: Concepts and Benchmarks

2004· article· en· W778010584 on OpenAlexaboutno aff
Marc L. Miller, Sung-Gwi Kim

Bibliographic record

VenueJournal of International Logistics and Trade · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicCruise Tourism Development and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPort (circuit theory)TourismAmenityMetropolitan areaRecreationDestinationsSustainabilityBusinessTourism geographyMarketingRegional scienceGeographyPolitical scienceEngineeringFinance

Abstract

fetched live from OpenAlex

In concert with an ambitious national agenda that emphasizes free trade and globalization, lncheon Metropolitan City is taking the first steps toward reinventing itself to become a twenty-first century “Pentaport” with integrated Seaport, Airport, Technoport, Business Port, and Leisure Port components. The lncheon Pentaport transformation-projected to be complete by 2020-will entail significant industrial, sociological, and institutional modification. Leisure Port objectives can be achieved through responsible planning attuned to the ideal of sustainable development and by empirical studies of lncheon tourism and leisure dynamics. International benchmarks of leisure port success are found in Sydney, Australia; Vancouver, Canada; and San Diego, USA, among seven other cosmopolitan cities. Growth estimations for coastal ferry passengers; beach use; recreational vessels and yachts in the lncheon region are encouraging. lncheon Leisure Port development of ten amenity destinations will require equal and multidisciplinary attention to questions of tourism design and tourism impacts. Important issues will concern environmental quality, clean shipping practices, the proper balance of modem and traditional amenities and attractions, trade-offs of cultural homogeneity and cultural diversity, and creative destination branding and marketing, among others.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.151

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.314
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations0
Published2004
Admission routes1
Has abstractyes

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