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Record W2384666871 · doi:10.1163/15691497-12341393

Global Cities and Housing Dilemmas

2016· article· en· W2384666871 on OpenAlexaff
Elham Fallah Manshadi, Afrooz Fallah Manshadi

Bibliographic record

VenuePerspectives on Global Development and Technology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Urban Networks and Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGlobalizationPhenomenonEconomic globalizationEconomic systemImmigrationDevelopment economicsGlobal cityEconomicsEconomic geographyEconomic growthPolitical scienceMarket economy

Abstract

fetched live from OpenAlex

Globalization is one of the outcomes of extended economic development in recent decades, which inevitably has direct and indirect effects on different aspects of human life. This paper explains the effect of globalization on housing dilemmas in global cities or cities that want to be global. For this phenomenon, the effect of immigration—resulting from globalization and space polarization, the economic influence of globalization on housing as a global good, the effect of globalization on cultural characteristics, and finally changes in urban space structures emerging from globalization—on site selection of residential land use will be analyzed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.018
Scholarly communication0.0050.006
Open science0.0000.008
Research integrity0.0020.002
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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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