مطالب

Cet article examine la représentation théâtrale du mariage sous l’influence des idées féministes. Notre étude, basée sur la revue d’une diversité de saynètes et de pièces de théâtre, et se référant aux témoignages de sociologues et juristes, montre que l’institution du mariage est interprétée durant la première moitié du XXᵉ siècle, non comme un pacte d’amour, mais comme un mécanisme d’aliénation, symbolisant soit l’esclavage de la femme, soit sa transformation en objet de marchandise. En effet, le théâtre féministe français s’inscrivant dans un contexte d’émancipation féminine liée aux courants socialistes et anarchistes, présente une critique exagérée du mariage, voire une remise en question totale de cette institution comme instrument de domination et de régulation sociale des femmes. Cette étude permet également de souligner le rôle du texte littéraire en tant qu’espace de contestation des normes sociales, et de réfléchir sur la possibilité de prendre en considération la fiction comme document anthropologique ou sociologique.

In this study, in which a new business model was constructed to examine the reflections of digitalization on the field of authentication due to the increasing importance of digitalization day by day. This paper aims to design a business model for digital transformation using Near-Field Communication (NFC) technology to develop foreign markets for original products by creating a product authentication database. Given the global use of NFC technology for authenticity checks and market development, this research is pioneering in proposing a business model for applying this approach to authenticate original products in Iran. Beyond product authentication, this approach can facilitate extensive market research, particularly in international markets, where many handicraft and clothing products are highly successful but often overlooked by industry owners. Following a description of Osterwalder’s business model, a business model canvas is developed, and service and sales revenue models are presented. The service revenue model includes two business strategies: "service provision per tap" and "annual subscription strategies (Bronze, Silver, and Gold)".

Purpose: In the 21st century, digital libraries have emerged in new ways in the professional career of librarians and other library users worldwide. The aim of the present study is to identify the functions of artificial intelligence in digital libraries. Method: This research is a qualitative systematic review. The population of the study includes all quantitative and qualitative research articles on the identification of artificial intelligence functions in digital libraries. Findings: A total of 500 research titles were retrieved through a multi-stage search in internal and external databases. Following a three-stage monitoring process (based on title, abstract, and full-text study), 34 research sources (9 foreign research titles and 25 domestic research titles) in the form of published journals articles and conference papers were identified and analyzed using thematic content analysis. For qualitative evaluation of the studies, 8 questions were posed to the experts, resulting in 1 selective code, 8 central codes and 42 open codes. Conclusion: The results of this research show that artificial intelligence can play an important role in the functioning of digital libraries and providing services to users. The findings demonstrate that AI-based systems are useful in various areas such as reference services, database search, organization, indexing, collection management, information retrieval, convenience and development, planning, and circulation. Moreover, librarians can enhance the quality of their works by employing this technology, which contributes to user satisfaction and the improvement of library services.

Background: Since the advent of modern policing, technological innovations in communication and information management have significantly shaped investigative practices and crime detection strategies. Aims: The current research study explores the transformative role of Artificial Intelligence in modern crime detection and prevention across diverse domains including cybercrime, environmental crime, financial fraud, and urban surveillance. Methodology: Employing a qualitative meta-synthesis methodology, the research critically examines peer-reviewed literature published between the years 2015 and 2025 to identify emerging trends, technological innovations, and socio-legal implications associated with AI-driven policing. Findings: The key findings highlight the integration of machine learning, computer vision, and natural language processing techniques into the predictive and real-time law enforcement systems. These technologies have demonstrably enhanced the accuracy, efficiency, and responsiveness of crime prevention strategies. However, the current study also reveals significant challenges, including algorithmic bias, lack of transparency, and inadequate regulatory oversight, particularly in socially stratified or underregulated contexts. Conclusion: The current article underscores the necessity of embedding explainability, accountability, and human oversight into Artificial Intelligence systems to ensure the ethical and equitable implementation of AI-driven policing systems.

This study examines how news headlines about the October 7, 2023, Gaza crisis employ linguistic structures to convey predetermined framing and reinforce power dynamics. Drawing on Information Structure Theory and the analytical framework of information packing theory, a corpus of 50 headlines from major international outlets (The New York Times, Reuters, CNN, AP, BBC, The Guardian, Al Jazeera) published between October 2023 and July 2025 was analyzed using qualitative discourse analysis. Information Structure Theory examines how speakers and writers organize and highlight pieces of information in sentences, such as what is presented as known or new, important or backgrounded, to guide the listener or reader’s attention and interpretation. The study investigates how syntactic and grammatical choices frame events, highlight causes, assign or obscure responsibility, and shape readers’ interpretations and thematic focus. Findings reveal that headlines systematically manipulate information structures to achieve pragmatic effects. Here, foregrounding (preposing) emphasizes key actors or consequences; postposing constructions activate presuppositions and dramatize urgency; passive voice, inversion, and interrogatives obscure responsibility and subtly assign or obscure blame; also, expansion constructions (relative clauses, appositives, and parentheticals) enrich context and amplify humanitarian or emotional dimensions. Overall, the study shows that linguistic choices function as pragmatic tools for managing discourse, framing narratives, and influencing perceptions of accountability. These results underscore the ideological and power dynamics embedded in news production and highlight the importance of analyzing information structures to understand how media discourse shapes public understanding and meaning.

The aim of this paper is to examine both the potential and limitations of Hegelianism in contemporary epistemology. To achieve this, the paper first explores Robert Brandom's interpretation of Phenomenology of Spirit in his 2019 work, Spirit of Trust. In this context, Hegel is positioned as a precursor to the holistic, historical, and social dimensions of belief, as well as a critic of the empiricist intuitions prevalent in modernity, aligning with the framework of American inferentialism. This section demonstrates that it is possible to discuss the constitution of concepts without invoking sensations or immediate knowledge. The paper then turns to the reception of Brandom’s proposal by scholars such as Richard Rorty and Slavoj Žižek, who concurs that Brandom falls short in maintaining a radical stance toward empiricism, and highlight the ethical and political challenges inherent in Brandom’s neo-Hegelian inferentialism. In this section, it becomes evident that Brandom’s concept of the Hegelian absolute and his notion of remembrance cannot be reconciled with a conception of reality as negative and contingent, a view that assumes progressiveness—something Žižek, in contrast, succeeds in recognizing within Hegel's philosophy.

Purpose : This study systematically reviews the advantages and disadvantages of using ChatGPT in higher education. Method : This systematic review adheres to PRISMA guidelines. The search was conducted using the terms "ChatGPT" and "chatbot" for the years 2021–2024 in Google Scholar, ResearchGate, Web of Science, and PubMed via Publish or Perish (version 8). A total of 365 records were retrieved, and after screening, 35 relevant studies were included. Findings : The analysis indicate that 66% of the reviewed studies highlighted the benefits of ChatGPT in higher education, including enhancements in cognitive and learning skills, support for research and writing, improvements in language and communication, and automation of certain tasks to increase efficiency. Additionally, advantages such as 24/7 availability, quick responses, topic diversity, privacy, and easy access to past interactions were noted. Among the advantages that received the most attention are optimization of academic training, enhancement of cognitive and learning skills, and assistance in the research and development process. However, 75% of the studies discussed disadvantages, including concerns about plagiarism, ethical issues, negative perceptions, lack of audiovisual communication, absence of human interaction, technical limitations, and restricted multi-dimensional engagement.  Among the most prominent disadvantages are ethical concerns, plagiarism, and lack of uniformity in responses. Conclusion : While ChatGPT offers significant benefits in education, its limitations require careful consideration to ensure responsible and effective use. Specifically, to address these disadvantages, practical measures such as the development of policies and ethical guidelines should be implemented to ensure responsible and optimal use of this technology in education.

In this research, first the financial criteria used in capital decision-making were identified and refined, then the most effective criteria were selected based on the deep learning algorithms including: RF, XGBoost, and LightGBM. In this stage, 11 factors were selected from the 35 factors found in previous research. In the next stage, based on the Forensic-Based Investigation algorithm (FBI), feasible investment options were identified and the internal rate of return was calculated over a 5-year period, and 42 companies that had an internal rate of return higher than the risk-free investment were selected as feasible investment options. During the next stage, different random combinations were used as investment portfolios using three methods: equal weight allocation, mean-variance model, and hierarchical risk preference model. Investment weights were determined for each invested share (combination) and investment returns were evaluated using different metrics. Finally, in order to validate the findings, the feasible investment options were divided into two categories of companies active in the financial industry and others, and the superiority of decision-making (higher returns) in a dynamic process was accepted.