Housing preferences and the image of inner city neighbourhoods in Budapest
Bibliographic record
Abstract
The study presents an analysis of inner-city neighbourhoods of Budapest. The major fi ndings are as follows: (1) The real estate prices increased in all parts of the inner-city in the last decade but the rate of change was varied. The most deteriorated quarters rapidly developed because of the reconstructions and the new constructions, however the highest prices are still recorded in the traditionally most prestigious neighbourhoods. (2) The social structure of the inner city signifi cantly changed. The new inhabitants – who moved to the inner city aft er 2000 – are younger, more educated than the traditional inhabitants who did not leave the inner-city aft er 1990. The reasons for moving into the inner-city are diff erent in the two groups. The location became the most important factor, and some special quarter related reasons emerged (good reputation). (3) The inhabitant’s views about the inner-city also transformed, mainly because the housing preferences of the old and new inhabitants are diff erent. The older inhabitants have a more critical att itude toward the inner-city than the new ones. The family house in the suburban greenbelt is their most preferred housing type. The satisfaction with the neighbourhoods depends on mostly the condition of buildings and the new functions of the quarters. The emergence of diff erent social groups in the neighbourhood is already perceived by the local population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".