Revitalisation of the Main Street of a Distinguished Old Neighbourhood in Istanbul
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.
Bibliographic record
Abstract
Abstract This study investigates the revitalisation of the main street of Beyoglu, which was the westernised part of Istanbul's CBD in the nineteenth century. Beyoglu started to develop in the sixteenth century with the introduction of embassy buildings of European countries. Its development reached a climax during the nineteenth century as a result of increased European trade and cultural influence, remaining the most distinguished quarter of Istanbul until the 1960s. Thereafter, it suffered from decay, disinvestment and abandonment as a result of later suburbanisation and the multi-centre development of Istanbul. Revitalisation of the quarter started with the pedestrianisation of the main street. This study investigates the functional transformation and changes in land prices along the main street and surrounding neighbourhoods after the pedestrianisation. The factors which effect land prices are investigated by the use of regression analysis. According to the results, access to mass transit is the most important factor. Besides its convenient central-city location, with easy access to the city's main transportation arteries, no doubt also its distinguished architectural character contributed to its revitalisation. Although the revitalisation of the main street as a cooperative movement of public and private sectors, effectively, it was a market-lead restructuring afterwards. At the same time, international companies opening up stores reflecting the globalisation movement increased the attractiveness of the main street. The results of the study can be used by urban planners, policy-makers and investors for the revitalisation of other historical neighbourhoods in Istanbul and other cities. For further research, hierarchical analysis of spatial impacts of revitalisation areas is suggested.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it