MétaCan
Menu
Back to cohort
Record W3082440050 · doi:10.1177/0042098020945247

Transnational gentrification: The crossroads of transnational mobility and urban research

2020· article· en· W3082440050 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUrban Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsSt. Thomas University
FundersUniversity of Warwick
KeywordsGentrificationUrbanizationEconomic geographyConsumption (sociology)GlobalizationReal estateValue (mathematics)Order (exchange)Economic growthSociologyGeographyEconomicsMarket economySocial science

Abstract

fetched live from OpenAlex

This introduction to the special issue introduces the contributors’ articles and identifies key themes relating to how increased transnational mobility has affected urbanisation processes in many cities, resulting in the globalisation of rent gaps. A mix of local and transnational real estate interests work to attract higher-income lifestyle migrants and tourists, often from higher-income countries to lower-income urban space in order to increase its exchange value. In the process, however, they act to reduce the use value of urban space to lower-income residents. The introduction notes that the acceleration of lifestyle mobilities moving through urban spaces, and the development of transnational lifestyles of urban place consumption, have produced new forms of gentrification – not merely the spread of an urban strategy to new cities, but the planetarisation of rent gaps. Transnational gentrification is the form of contemporary urbanisation that occurs as a result of closing these rent gaps through attraction of higher income, transnational migrants, often from high-income countries in Northern Europe and North America.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score1.000

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 studies0.0010.002
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 head0.155
GPT teacher head0.401
Teacher spread0.246 · 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