Abdolkarim Soroush’s thought is regarded by some researchers as a turning point in contemporary Islamic reform discourse. This article concerns Soroush’s epistemology as a determining factor in this paradigm shift and interprets this shift as an epistemological turn in Islamic reform discourse, shifting from ›Islamic genealogy of modernity‹ to rationalization of Islamic methodology. After a short introduction to Soroush’s intellectual biography, this article will isolate neorationalism or neo-Mu’tazilism, religious post-positivism, historicism, hermeneutics, and dialogism as main features of Soroush’s epistemology. This (...) paper suggests that rationalism as reasoning independent from revelation and non-essentialism are two main determining pillars of Soroush’s epistemology. In the conclusion, I shortly compare Soroush’s thought with some other contemporary Muslim reform thinkers and discuss how and why Soroush’s thought can be interpreted as an epistemological turn in Islamic reform discourse. (shrink)

In this paper, I show that there is a bidirectional relationship between gender-based social norms and gender-segregated education policies that excludes girls from knowledge production within the Iranian school system. I argue that gender segregation in education reproduces hermeneutic inequality through the reinforcement of epistemic segregation as a form of epistemic injustice. In particular, I focus on gender-based instructional epistemic injustice, which refers to a set of epistemic practices that actively exclude a student or an education professional in their capacity (...) as a knower from the process of knowledge production within an education system based on gender dynamics, roles, norms, or expectations. This, in addition, has an impact on schoolboys through the reproduction of active ignorance. I conclude that in societies such as Iran, where highly gendered norms play out in the school system and are further reinforced by that system, the result is not limited to gender segregation itself, but extends beyond it to a form of epistemic injustice that wrongs students by reproducing and reinforcing those highly gendered norms. (shrink)

To date, technology has become so integral to our lives that it is almost impossible to imagine a day without using it. The digitization of society is gaining speed every day, affecting all areas of life: communication with people and the management of entire governments. To one degree or another, the use of digital technologies can be observed in every social institution on which society is built. The process includes social changes associated with introducing modern technologies into society and social (...) control. Since the second half of the XX century, the introduction of digital technologies has been seen as a means of overcoming temporal and spatial restrictions, the negatives of subjectivity that hinder the development of modern society. In the XXI century, the influence of digital technologies has grown significantly, which calls into question the sovereignty of the person himself as a social object. Undoubtedly, technology makes our lives much more accessible, with benefits such as saving time, accessing new information, and simplifying everyday life. However, the more social space is captured by objective digitalization, the more this space undergoes subjective influence. Digital technologies do not liberate the person from subjective control but, on the contrary, contribute to it. In the article, we consider how this happens in the field of the major social institutions of society, and possible vital consequences of this impact. (shrink)

Breast cancer is the leading cause of death among women with cancer. Computer-aided diagnosis is an efficient method for assisting medical experts in early diagnosis, improving the chance of recovery. Employing artificial intelligence (AI) in the medical area is very crucial due to the sensitivity of this field. This means that the low accuracy of the classification methods used for cancer detection is a critical issue. This problem is accentuated when it comes to blurry mammogram images. In this paper, convolutional (...) neural networks (CNNs) are employed to present the traditional convolutional neural network (TCNN) and supported convolutional neural network (SCNN) approaches. The TCNN and SCNN approaches contribute by overcoming the shift and scaling problems included in blurry mammogram images. In addition, the flipped rotation-based approach (FRbA) is proposed to enhance the accuracy of the prediction process (classification of the type of cancerous mass) by taking into account the different directions of the cancerous mass to extract effective features to form the map of the tumour. The proposed approaches are implemented on the MIAS medical dataset using 200 mammogram breast images. Compared to similar approaches based on KNN and RF, the proposed approaches show better performance in terms of accuracy, sensitivity, spasticity, precision, recall, time of performance, and quality of image metrics. (shrink)