نشریه نامه معماری و شهرسازی
سال هفدهم شماره 45 (زمستان 1403)

This research examines conflict in the discourse of spatial planning in Hamadan City through an agonistic lens, moving away from consensus-based approaches like those of Habermas. By utilizing Mofe's theory of agonistic and antagonistic fields, the study seeks to understand how discourse conflict can impede urban development, distinguishing between conflicts that result in conflictual consensus (agonistic) and unproductive conflicts (antagonistic). The analysis underscores the detrimental effects of antagonistic discourse fields on urban development processes in Hamadan, highlighting how discourse competition shapes perceptions of urban development as non-productive and anti-developmental. By differentiating between agonistic and antagonistic fields, the study seeks to understand how discourse competition contributes to an anti-development process, emphasizing the impact of antagonistic discourse fields on urban development in Hamadan. This analysis utilizes two databases from Hamadan Payam and Hegmataneh newspapers to examine the discourse field and contradictions surrounding urban development in Hamadan. Many studies, particularly those by Fairclough, highlight that media and newspapers are the most effective sources for uncovering hegemonic and meaning relations. Accordingly, this research collected and analyzed textual data from 2017 to 2024 regarding urban development in Hamadan. This analysis employs multi-perspective discourse analysis, integrating discourse theory and topic modeling to examine the spatial planning discourse field of Hamadan City. This analysis operates on two levels: macro and micro. At the macro level, we analyze the mechanisms of meaning generation, discourse relations, and the prevailing ideological foundations. At the micro level, we utilize text mining tools like RapidMiner for topic modeling and discourse themes, which are crucial for uncovering the text's hidden structures and language use. The research findings indicate that each period of the discourse field features three distinct discourse structures, each interpreting urban development through different genres. Despite these genre differences, all discourses operate within a shared territory and limits shaped by the prevailing discourse order of each period. The reformist political discourse in the fifth period and the fundamentalist discourse in the sixth period establish the territory and ideological foundation that compel the discourses to align or risk exclusion. The findings suggest that two competing political discourse orders in each period influence how urban development is interpreted. This competition creates a structural duality, meaning that the interpretations from each period are fundamentally different and stand in opposition to one another, rather than working together or complementing each other. The significance of this opposition is explored through an analysis of the practices associated with urban development and how these practices are represented in physical spaces. Essentially, the study looks at how the differing political ideologies shape the understanding of urban development and the actual practices and representations in the urban environment, highlighting the impact of political discourse on the built environment. Finally, this research showed that the confrontation of two discursive orders has turned the field of urban planning into an antagonistic and non-productive field, where planning policy has become political planning that reverses the development process.

Nowadays, discussion about corruption at the network level across various policy domains are common, whether in the scientific-specialist debates or in the political and social ones. This research focuses on the issue of the formation and mechanism of networked corruption in the gardens of Tehran metropolis. It addresses three levels of the formation of network corruption, the structure of network corruption, and the mechanism of exercising power and distributing its benefits in an exploratory process. The methodology of the current article is qualitative and based on the constructive grounded theory. Accordingly, semi-structured and in-depth interview were conducted with 20 people from the five main groups related to the current research. Based on the results, the fields of legal, organizational-administrative and economic formation have been identified. Then, the structure of network corruption has been explained in two major categories of known and recognized networks against unknown and unrecognized networks with their following models. This study also discusses and investigates  the mechanisms of exercising power and distributing its benefits in these networks. Whether through prevention or dealing with network corruption in various policy areas, it seems vital to discover and explain the factors and processes of the three levels mentioned. It seems that one of the most effective ways to prevent and deal with complex organized corruption that has taken the form of a network is a deep understanding of the processes, mechanisms, relationships and how decisions are implemented among network members. Therefore, this research has focused on three basic issues in network corruptions formed in the gardens of Tehran metropolis. Although various other fields can be mentioned in the formation of network corruption, including institutional, ethical, sociological and psychological dimensions, this research paid more attention to the issue of corruption in gardens rather than the administrative-organizational aspect, while also considering other legal and economic aspects. One of the main contributions of this research is the separation of the types of network corruption into two types: known and formalized networks versus unknown and informal networks and the types of models under it. This separation is reflected in the form of tight and loose relationships between members. Based on this duality, a variety of models of exercising power and distributing benefits among network members were identified, which can be classified in the dual form of immediate and future compensations. One of the topics that needs further exploration is the way of formation and especially the types of network corruption in other urban areas, and the examination of commonalities and differences compared to the findings of this research. As more studies and cumulative findings are conducted on this specific and complex multi-stakeholder phenomenon, there is hope for the development of policies that effectively address it. This would enable more informed decision-making and implementation within different policy-making processes.

Urban participation, as one of the new approaches in urban planning, has received substantial attention in studies in recent decades, and the necessity of using it in urban plans and programs has been increasingly emphasized. Due to the importance of this issue in urban planning, it is necessary to identify the barriers and facilitators to realizing participation, despite the occasional mention of these cases in related research, the barriers and facilitators of participation have not been mentioned in a special and focused way. In this regard, this article, by reviewing domestic and foreign articles in the period from 2000 to 2023, has categorized the barriers and facilitators to the realization of participation. In this research, with a systematic review, 148 articles were examined in two external databases (Science Direct and Google Scholar) and three internal databases (NoorMags, Comprehensive Humanities portal, SID). After reviewing all the articles, 50 less relevant articles were discarded, and the remaining 96 articles were used to extract the codes. In order to analyze the concepts obtained, qualitative content analysis was used. Finally, the barriers to the realization of participation were categorized into individual, semantic, content and process, and institutional subcategories. Individual barriers included issues such as people's disappointment, frustration, discouragement, indifference, feelings of no need to participate, disinterest in participation, disbelief in its efficacy, feelings of rejection, and experiences of discriminatory treatment. Semantic barriers involved the diversity and lack of official definitions, ambiguity in defining participation, the non-popularity of the concept, its dependence on other concepts, as well as the complexity and non-native nature of the concept itself. Content and process barriers included high decision-making costs, time-consuming participation processes, a large number of stakeholders, lack of infrastructure, and unfair distribution of services. Institutional barriers were characterized by conflicts between the government and the people, inefficient institutional systems, lack of access to information, poor coordination with the public sector, overly rigid laws, and uncontrollable factors. In the results obtained from the review of the initial codes, it was found that individual, social and institutional contexts influence the realization of participation, and the realization of participation in a society depends on creating a culture of participation in society and related institutions, as well as providing the appropriate infrastructure for the realization of participation.

Urban planning and design issues are highly complex, making it challenging to achieve a comprehensive understanding of these issues, especially on a large scale, using traditional urban planning methods alone. Therefore, the integration of data science and modeling presents a promising approach for comprehending urban issues. Extensive research and reports on real urban projects implemented across various countries suggest that machine learning and deep learning techniques have the potential to effectively address urban problems and offer additional benefits such as reducing economic costs associated with inefficiencies, improving operational speed, and enhancing predictability. The integration of machine learning and deep learning can be utilized in the evaluation, design, and post-implementation stages of urban planning and design processes. User experience, including environmental stress, happiness, and fear, significantly influences the character and activities within urban spaces. Hence, it is crucial for urban designers to create new spaces or revitalize existing ones in a way that evokes a positive emotional response and a sense of belonging among users. Numerous studies have explored this subject, primarily focusing on evaluating people's emotions within physical environments and occasionally within virtual settings, using AI-based methodologies. Sentiment analysis or opinion mining, previously employed before the rise of social media, is now being investigated and analyzed using computational methods with the aid of vast amounts of data published on social media platforms. This research domain, widely used in economic, marketing, political, and social research, has increasingly permeated the realm of urban studies. However, it is relatively new within the field of urban studies, with only a limited number of research studies conducted thus far. The main objective of this research is to develop a predictive model for understanding users' emotional responses towards urban spaces through an analysis of multi-modal data, including images and textual content, published in virtual spaces. This study incorporates two notable innovations:The use of a machine learning approach in sentiment analysis of multi-modal data on an urban scale, which has been explored in data science research but remains insufficiently explored in the realm of urban planning and management in Iran. The creation of a dataset comprising textual and visual data relevant to urban environments. It aims to present a predictive model that effectively analyzes sentiment in textual and visual media data derived from Twitter. The research employs a quantitative methodology and utilizes a supervised deep learning technique. The case study encompasses multi-modal urban data from eight megacities in Iran, collected over a ten-year period until December 2021. An algorithmic hybridization based on the Convolutional Neural Network (CNN) architecture has been developed and employed to train the textual data, resulting in an accuracy rate of 77%. Additionally, the visual data has been trained using three distinct algorithms, with VGG19 demonstrating superior performance and achieving an accuracy rate of 88%. A hybrid algorithm has been devised to train the multi-modal data, yielding an accuracy of 66%. Subsequently, a combination model leveraging pre-trained VGG19 models alongside the developed text combination model has been implemented, achieving an elevated accuracy of 81%. These outcomes demonstrate the machine's capacity to predict sentiment polarity in textual-visual data related to cities.

Interventions related to the structural restoration of architectural heritage, which aim to both protect human lives and preserve cultural property, can create more and broader risks compared to other types of restorative interventions for continuity of the historic buildings and the safety of their users. Therefore, designing and implementing structural interventions based on clear and applicable theoretical foundations becomes necessary. However, it seems that the existence of a level of overview of theoretical issues and a lack of clarity in the understanding and applying guiding principles have confused the restorers and structural engineers. This confusion complicates etablishemnt of a proper connection between the theoretical topics and practical interventions. From this point of view, the research has investigated the written recommendations of the experts in this field in order to find applicable guidelines and recognize the challenges facing their proper application in connection with structural interventions of architectural heritage. The experts selected for this study have an international reputation in related fields, practical experience and have authored Authentic written research on this topic. The research is applied in terms of purpose and follows a qualitative approach. The required data was obtained through library studies relying on the written sources of selected experts, and the data analysis has been done based on the content analysis of these sources and with the help of the software analysis technique with MaxQDA software. The research results include a) conservative and technical guidelines related to the proper orientation of structural interventions, b) the challenges of applying these theoretical guidelines and c) solutions to overcome these challenges. Conservation guidelines include conservation of values, maximum conservation of authenticity, compatibility of materials and techniques, conservation of structural integrity, compliance with conservation goals, balance of attitude, degree of similarity of action, distinctiveness of action, minimum possible intervention and relative reversibility of action. Technical guidelines can also be divided into key aspects: adaptability to the status qua, structural efficiency, feasibility, controllability, maintainability, durability of intervention and the final outcome measurement of the action. Also, the challenges facing the application of these guidelines are divided into three categories: 1) challenges affected by the contradiction between the philosophy of conservation and the requirements related to the safety level, 2) internal conflicts between some of the conservative guidelines and 3) the challenges caused by the impact of some external issues such as financial resources on interventions. To overcome these challenges proper structural restoration should be presented with attention to points such as the need to review and establish specific standards and risk levels for historical structures, perform accurate and combined diagnostic studies before deciding, exercising humility in choosing less destructive modern solutions with greater reversibility, using an incremental approach to determine the minimum possible intervention, applying lower levels of reliability and considering parallel arrangements to minimize the possibility of structural failure and use sustainable financial resources without applying external pressures.

A substantial body of research has been conducted on the subject of housing evaluation indicators. Given the extensive nature of the research, the presentation of a unified framework and the evaluation of the aforementioned set of indicators represents a crucial step forward in the field of housing research. This classification provides the most effective indicators for housing design and evaluation for design, planning, and housing research professionals. This article aims to evaluate the indicators of quality in residential complexes, with a particular focus on social interactions as a fundamental aspect of residents’ lives. Consequently, the objective of this study is to assess and review the elements and indicators associated with social interactions in residential complexes. The current research approach is qualitative and is based on the synthesis research methodology, as proposed by Robertash (2007). To conduct a more comprehensive evaluation, it is necessary to consider several key factors, including quality of life in housing, housing satisfaction, housing quality, user satisfaction, resident satisfaction, residential satisfaction, occupant satisfaction, social interaction, social relationship in housing, neighborhood interaction in housing, sociopetal space in housing, and co-presence in housing. The mentioned keywords should be used to search for relevant research and papers. The research community encompasses 290 articles published in reputable scientific journals between 1999 and 2023. The articles address the topics of housing evaluation indicators and social interactions in housing. Papers evaluated based on an evolution checklist must contain a case study or other relevant examples, the purpose of the paper, a description of the research method and the evolution method employed, the findings, and the result. Ultimately, the research sample consisted of 54 scientific research articles that were collected to form a representative sample. In the initial phase of analysis, open codes are placed close to one another, allowing for the overlapping and semantically related items to be re-coded and combined. This process facilitates the extraction of core codes. As a result of this process, the main dimensions and selected codes for social interactions in residential complexes are successfully identified. Data analysis revealed that the interaction components in residential complexes could be classified into seven dimensions and 19 factors. The interaction components are open space (natural features, size and area of public open space, open space per capita), spatial configuration (open space location, integration and enclosure, diversity, audio and visual comfort, balconies, privacy, and path), activities and behavioral settings (e.g., diversity and domains of activity, flexibility and adaptability of space and activity, and furniture and environmental features), aesthetics (e.g., aesthetical aspects, readability, and place attachment), safety and comfort, resident characteristics and culture, and management of residential complexes. The results of the literature review have been used to construct a model that represents the relationship between the main components. This research also focuses on architectural aspects of the residential complex, including open space, spatial configuration, behavioral settings, safety and comfort, and aesthetics, and presents a model.