The Impact of Morphological Shifts in the Historical Fabric on Attachment to Place in Post-Conflict Cities: A Case Study of Old Mosul
Bibliographic record
Abstract
This research aims to analyze the impact of morphological transformations on the historical urban fabric of Old Mosul following the armed conflict and explore how these transformations affect residents' levels of place-related connection.Place-related connection is considered a crucial psycho-social indicator for understanding patterns of return, resettlement, and the reconstruction of urban identity.The study is based on the fundamental premise that reconstruction is not limited to rebuilding buildings, but also encompasses rebuilding the relationship between people and place, including collective memory, identity, and social bonds.The study employed a mixed-methods approach, including spatial analysis using geographic information systems (GIS) to compare changes in the urban fabric between 2014 and 2023.It also utilized a field survey of 120 participants to measure dimensions of placerelated connection according to the Scannell and Gifford (2010) model and semi-structured interviews with a representative sample of residents and specialists.Data were analyzed using descriptive statistics, Pearson's correlation coefficient, and linear regression analysis.The results showed a high level of spatial identity and social cohesion, contrasted with a low level of spatial dependency.This reflects the population's attachment to the historical memory and symbolism of the place, despite the deterioration of its functional and service infrastructure.The results also revealed a significant negative correlation between the extent of urban damage and levels of spatial attachment (r = -0.61,p < 0.01), while urban transformation explained 37% of the variance in spatial attachment according to the regression model (R² = 0.37, p < 0.001).These findings confirm that the connection to place remains strong, both emotionally and socially.However, its sustainability requires the reactivation of urban spaces, the revival of traditional functions, and the improvement of infrastructure services.The originality of this study lies in its provision of an analytical framework that combines spatial and psychosocial methodologies to understand the dynamics of reconstruction in post-conflict cities.It also contributes to enriching Arabic literature in the field of urban planning and heritage by providing an applied model that can be used in other cities with similar conditions and by directing urban policies towards a human-spatial approach based on identity, memory, and social relations, and not just on physical reconstruction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".