Memory-linked placemaking in urban heritage places: İstiklal (Jewish) Quarter, Ankara
Bibliographic record
Abstract
Memories formed by people’s experiences in the place reveal insights about how the built environment is identified with people. These memories are reshaped in time with the uses and meanings attributed by people to the physical environment in urban heritage places. The changes both at the physical and social levels require re-understanding, re-considering, and re-evaluating these relationships from today’s perspective. In this sense, the thesis aims to consider memory and memory places linked with the placemaking approach to understanding the evolving relationships in urban heritage places.\nThe İstiklal (Jewish) Quarter in Ankara chosen as the case study area, comprises layers of meanings over time formed by diverse communities, cultural frames, social backgrounds and memory practices. Social and physical transformations over time have led to physical deterioration processes in the built environment, which have resulted in a decrease in usage. The change in the relationship between people, place and memory in the İstiklal (Jewish) Quarter is a reflection of all these physical and social changes that have occurred. \nIn this context, the thesis primarily focuses on the reflections and discussions of the concepts of memory and placemaking in urban heritage places. Afterward, the process of understanding the physical and social transformation of the İstiklal (Jewish) Quarter from past to present covers the literature review, archival research and field study which includes observations and in-depth interviews. Finally, the policies, strategies and actions to be developed as part of the conservation process of the İstiklal (Jewish) Quarter are addressed with the memory-linked placemaking approach.
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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 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".