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Record W7048104971

Immigration of “quality of life” and partial exit: a study based on the cases of Mérida (Mexico) and Barcelona (Spain)

2018· article· es· W7048104971 on OpenAlexaboutno aff

Bibliographic record

VenueMagazine Portal Bibliotech Digital (Universidad Nacional de Colombia) · 2018
Typearticle
Languagees
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsGentrificationTourismResidenceImmigrationWork (physics)Distribution (mathematics)GlobalizationGlobal city
DOInot available

Abstract

fetched live from OpenAlex

The cities of Mérida (Mexico) and Barcelona (Spain) are located in regions with strong tourism associated with their heritages, their climatic conditions and their coastal locations. In addition, they attract those living in neighboring countries with higher costs of living because of the better climate and the more affordable costs of living which permit a “great lifestyle”. Given these conditions, middle-class persons from the United Statesand Canada, in the case of Mexico, and from France, Germany and England or other EC countries, in the case of Spain, without work obligations in their country of origin (because they are retired or have some income), take up residence in these cities. As well, the development of off-site work and economic globalization has contributed to the increased mobility of businesses to other countries. These socio-economic factors along with a particular residential and tourist production strategy in these regions give rise tosituations of tourism, partial exit and immigration. Using various quantitative and qualitative methodologies, this article analyzes the characteristics and territorial distribution ofmiddle class international migrants in both cities as a starting point to study the impact of this phenomenon on gentrification and residential segregation. The results obtained in both cities are similar. Both cases deal with continuous growth, with the migration of middle classes increasing in importance and visibility, reinforcing and increasing the existing residential segregation in these cities.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.273
Teacher spread0.248 · 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
Published2018
Admission routes1
Has abstractyes

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