Gentrification in the Athenian Context: the Gas Neighbourhood Case Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".