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Record W4396723877 · doi:10.1080/14747731.2024.2343452

Cultural globalization at sea: the rise of the modern Caribbean cruise industry

2024· article· en· W4396723877 on OpenAlexafffund
Shayan S. Lallani

Bibliographic record

VenueGlobalizations · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCruise Tourism Development and Management
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCruiseGlobalizationEconomyPolitical scienceEconomic geographyGeographyEconomicsMarket economyOceanography

Abstract

fetched live from OpenAlex

Carnival, Royal Caribbean, and Norwegian—the largest cruise lines today—emerged in the late 1960s and early 1970s, advertising their packaged vacations to a growing audience of middle-class Americans interested in encountering cultural difference. This article argues that, beginning in the late 1970s and continuing into the following decade, the cultural representations that these mass-market companies leveraged drew on Eurocentric understandings of Caribbean societies, homogenizing those countries despite attempts to showcase difference. These companies also reimagined global cultures Eurocentrically in onboard themed experiences. As both a product and agent of globalization, the mass-market cruise industry selectively deployed referents in ways that increased the appeal of cruising as escapism while reducing the likelihood of cultural confusion and reassuring passengers of their comfort. Through these processes, companies produced cruise ships as metaspaces while simultaneously expanding the construction of metaspaces to ports as they gained economic and political power in the Caribbean. This process resulted in the erasure of cultural difference.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.012
Scholarly communication0.0090.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.022
GPT teacher head0.309
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2024
Admission routes2
Has abstractyes

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