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Record W1570121703

Gentrification in the Athenian Context: the Gas Neighbourhood Case Study

2006· preprint· en· W1570121703 on OpenAlexaboutno aff
Georgia Alexandri

Bibliographic record

VenueEconstor (Econstor) · 2006
Typepreprint
Languageen
FieldSocial Sciences
TopicContemporary and Historical Greek Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGentrificationContext (archaeology)Economic geographyGeographyPopulationPoliticsEconomyNeighbourhood (mathematics)Political scienceEconomic growthDevelopment economicsSociologyEconomicsDemographyLawArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Discourse on the phenomenon of gentrification has mainly focused on western cities of the US, Canada and the UK. However gentrification is experienced worldwide. Nonetheless as the socioeconomic and political context is different in each city, the process develops differently in each case with regard to the distinct background. However, research about gentrification in the Mediterranean region is limited. From this viewpoint this article deals with the gentrification process of the Athenian inner district of Gas. Although gentrification is privately led, the role of the State is crucial for the development and implication of this urban trend. Governments, central and local, facilitate this process and encourage private investments as in the short term they gain benefits and economic profits. However, in Gas the attraction of outside capital in special forms such as entertainment amenities overruns the local potential. This change in land-use results in the displacement of the local population, thus encouraging the conquest of the city's core by the middle and affluent income classes. The article highlights the process of gentrification in this inner city area of Athens. Its basic purpose is to draw some general conclusions of the gentrification process in the Southern European context of Athens.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.587
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.292
Teacher spread0.250 · 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 teacher head, not a consensus.

Study designObservational
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
Published2006
Admission routes1
Has abstractyes

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