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Record W7155750303

The Social Economy of Escaping to the Beach: The Impact of Privileged Lifestyle Migrants on a Local Community in Caribbean Costa Rica

2024· dissertation· en· W7155750303 on OpenAlexaboutno aff
Erin Adamson

Bibliographic record

VenueKU ScholarWorks (The University of Kansas) · 2024
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPrivilege (computing)ImmigrationEthnographyWork (physics)Consumption (sociology)Social classRemittanceInternal migrationSocial integration
DOInot available

Abstract

fetched live from OpenAlex

This study explores the social and economic impacts of Euro-American migration to the southern Caribbean coast of Costa Rica. This lifestyle migration from highly developed countries is a growing trend as U.S., Canadian, and European citizens seek to maximize their incomes in lower-cost locales, enjoy a rural-idyll near natural amenities, and live out the thrill of travel on an extended timeline. I examine how the wealth and privilege of Euro-American lifestyle migrants relative to local Costa Ricans reshapes communities, impacts migrant integration, and potentially incentivizes locals to adapt to migrants. In this research I use interviews, ethnographic observations, and media analysis during two periods of fieldwork in the south Caribbean. I find that social class and ethno-national differences prevent most Euro-American migrants from deep integration into local communities. While owning a business is considered a structural measure of immigrant integration, entrepreneurial lifestyle migrants in Costa Rica form a new owning class that serves to maintain separation from locals. I find that locals resist integration into the cultural expectations of migrants, but do adopt some aspects of migrant culture that help them find work in the tourist-oriented businesses run by migrants.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.190
Threshold uncertainty score0.377

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.290
Teacher spread0.274 · 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 routes1
Has abstractyes

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