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Record W2806884560 · doi:10.1111/area.12460

The gringos of Cuenca: How retirement migrants perceive their impact on lower income communities

2018· article· en· W2806884560 on OpenAlexafffund
Matthew Hayes

Bibliographic record

VenueArea · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsSt. Thomas University
FundersSt. Thomas UniversityThomas University
KeywordsEconomic impact analysisLow incomeDemographic economicsEconomicsPolitical scienceSociology

Abstract

fetched live from OpenAlex

This paper looks at the concern North Americans express about the impact their relatively higher incomes are having on lower income workers in Cuenca, Ecuador. North Americans who retire to Cuenca often perceive their impact to be minimal or benign, yet a large amount of discussion within the community of “expat” migrants is about different ways North Americans are affecting the local economy, and how to minimise these impacts. Of particular concern is the racialised price system that migrants perceive to be in effect. North Americans racialise their economic impact, seeing “gringo pricing,” rather than their higher incomes, as a threat to the receiving community. Participants evoked moral codes to discuss price levels, and sought to diminish their impact – not merely out of concern for Ecuadorians who might be displaced by higher prices, but out of a sense of ruining the authenticity of Cuenca, a UNESCO World Heritage site.

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)0.003
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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.003
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.305
Teacher spread0.271 · 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

Citations19
Published2018
Admission routes2
Has abstractyes

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