مطالب

The ongoing increase in the population of Kurdish as Heritage Language (HL) learners encouraged the present study to explore the learners’ motivations as well as the influential factors on its development. Second Language Motivational Self-System (L2MSS) was adopted as the theoretical framework wherein, the subscales of the Ideal-self, Ought-to self and Motivational Intensity were explored. The study drew on a mixed-methods design in which semi-structured interviews were conducted with four undergraduate participants and a total number of 213 undergraduate Iranian learners of Kurdish participated in a survey. The qualitative results indicated that the interviewees had a positive experience of learning Kurdish in the classroom and were more enthusiastic to get engaged in the process of learning in the future . Furthermore, the quantitative results indicated that the participants more often pursued Kurdish in terms of the Ideal self and that learning Kurdish revealed to be an opportunity to fulfill the learners’ wishes. It was also found that the male participants were propelled by stronger motivational force which was more probably due to stronger sense of identity among male participants.

The theoretical discussion of the present paper is particularly based on the insights of Giorgio Agamben contextualized in Iris Murdoch’s novel, A Word Child (1975), written in the transitional period of the seventies England. It will inspect Agamben’s biopolitical insights to examine how they may contribute to understanding of the dark side of sovereignty considering the figure of a banished individual. Taking the precariousness of the emotional, political and ontological faculties of ‘love’, ‘homo sacer’ and ‘bare life’ allocated to the human being in Murdoch’s novel, A Word Child , this paper offers a different view of Murdoch’s inspirational emphatic love, socio-political abstruse problems in her novel arguing that Agamben’s account of these issues supplies an underlying structure of the form-of-life. It resounds through Agamben’s view as a never-ending struggle of human beings to underpin the messiness and cruelty of life in which characters are emotionally engaged and entrapped in order to examine some potentialities as the escape routes from the prevailing deadlocks of the era and eventually to trace, according to Agamben, a form-of-life that is called a happy life.

Objective: Recent literature emphasizing the importance of income distribution for pollution. The GINI index is the most common indicator for measuring income inequality in previous studies. The new literature has focused on relative redistribution, which is quantified by the GINI coefficientis defined as the difference between the GINI based on market income and GINI based on disposable income. Thus, this study relies on the redistributive effect of taxes and transfers and its impact on carbon dioxide emissions.Methods: The study is conducted using aggregated data from oil-exporting countries including Canada, the United States, the UK, Mexico, the Netherlands, Russia, and China between 2010 and 2020 by using a simultaneous equations system consisting of two equations so that economic growth and pollution emission are as endogenous variables. Elative redistribution, good governance, oil income, trade openness, and CO2 emission are the exogenous variables. Results: Based on model estimates, income inequality, good governance, and oil income have a positive and significant impact on economic growth over the years studied, while inequalities in human development and population growth rates have a negative impact. Economic growth and trade openness also have a negative and significant impact on the spread of pollutionConclusion: Taxes and transfer payments, as redistribution tools can stimulate economic growth. Relative redistribution as a more equitable way can lead to increased economic growth and economic growth reduces carbon dioxide emissions. Therefore, providing an appropriate standard of income inequality can help to better understand and formulate effective policies for income equality.

Industrial development depends on planning and formulation of strategy and systematic policies. The purpose of this research is to analysis phase of conventional strategies in order to progress of Iran’s industry in the international atmosphere. The statistical community of this study is included of experts and academic pundits. To do this at first identification of significant conventional industry’s strategy was determined. six strategies was founded and then was specified, using the criticality of each phase’s approach. According to data analysis, efficiency of technology transfer on industrial progress is more than other elements. On the second rank, domestic and foreign investment’s strategies, development of parent industries, development of infrastructure industries and designing strategy and industrial policies and finally government support strategies has been placed at the lowest level that means third rank. Therefore technology transfer plan was recognized as the most important strategy and specially it should be considered as the strongest strategy for developing industry. The insight that this model offers to managers and decision makers of the country’s industry can help them to plane strategy for developing.

Objective: The stock market and the foreign exchange rate market have been sensitive segments of the financial market. These two markets are rapidly affected by fluctuations and business cycles in the economy and quickly reflect the economic change. At the same time, turmoil in one or both markets raises concerns among market policymakers. We also address the question of whether the national currency can be strengthened through the stock market.Methods: This study examines the stock market price on the value of the national currency of Iran using stock-oriented models and the Markov switching method in the period 1995 to 2021. In this study, the non-linear Markov switching method was used to estimate the model, and the LR- test method was used to check the linearity or non-linearity of the models. Akaike's test has also been used to determine the number of Markov switching regimes.Results: The research results show that for every one percent increase in stock prices, the exchange rate has decreased by 0.21 percent. Therefore, the results indicate the approval of stock-oriented models in the Iranian economy. In other words, the capital market is one of the determinants of the exchange rate.Conclusions: According to this model, lower stock prices reduce the wealth of domestic investors, which leads to lower demand for money with lower interest rates. Lower interest rates cause capital outflows to overseas markets, assuming other conditions remain stable, causing the domestic currency to depreciate and the exchange rate to rise.

Objective Using a quantitative approach and a systematic methodology, advanced structural equation modelling techniques were applied to test the research hypotheses. In a possible sample of 98 experts and activists of entrepreneurship in Sistan and Baluchistan province, the observations were collected using a standard 32-items tool based on Likert scale. After screening the raw data, covariance-based confirmatory factor analysis was used to evaluate the validity, reliability and fittingness of the research model, and the hypotheses were tested in the form of a structural model. The results of convergent and divergent validity tests showed that the two indicators of the research model has validity. Also, the reliability tests indicated the generalizability of the research results at 85%. Also, all the research hypotheses were confirmed.Objective Using a quantitative approach and a systematic methodology, advanced structural equation modelling techniques were applied to test the research hypotheses. In a possible sample of 98 experts and activists of entrepreneurship in Sistan and Baluchistan province, the observations were collected using a standard 32-items tool based on Likert scale.

This study examined the possible effects of orthographic/phonologic priming techniques on the receptive language skills of Iranian EFL learners with different proficiency levels. From an initial pool of 700 EFL learners from a language learning institute, two hundred and seventy learners from both genders were selected based on their performance on an English proficiency test and classified into six experimental and three control groups. After gaining certitude about the participants’ English proficiency levels, the semantic and orthographic/phonologic priming phase was conducted, and consequently, the participants’ contextualized comprehension of the primed words was assessed via a set of reading and listening comprehension tasks. The performances of the participants on the designed tasks indicated that semantic primes were more efficient for improving both comprehension skills compared with the orthographic-phonologic primes. Moreover, based on the results, language proficiency affected the success of the primes on both reading and listening comprehension tasks; advanced learners showed a greater improvement than the beginners and the intermediates under the influence of the priming techniques. Orthographic-phonologic primes were found to be more efficient for beginners, whereas the advanced learners showed an enhanced performance with regard to semantic primes. Overall, semantic primes showed more facilitative effects across various comprehension tasks due to their activation of deeper cognitive processing. Orthographic-phonologic primes were also successful. However, they were more efficient in the early stages of language learning, where visual recognition played a more critical role.

This research examines the Iranian digital community's engagement with the Metaverse, analyzing 14,724 tweets (expanding to 48,620 with retweets) from 23,571 unique users. Interest in the Metaverse among Iranians surged in the seven months following Facebook's rebranding but has since waned. A significant link between digital currency discussions and Metaverse topics was observed. Economic activists in the cryptocurrency market, forming the primary content creators, generally portray the Metaverse positively, focusing on earning opportunities. Another active group includes technology enthusiasts who share the latest Metaverse developments. Moreover, some users integrate Iran's socio-political context into their discussions, often contrasting Iran's technological stance with global giants like Facebook and addressing internet censorship. A distinct perspective comes from users wary of potential colonialist uses of technologies like the Metaverse, expressing apprehension about human subjugation. This sentiment forms the basis of most negative views on the Metaverse's development within the Iranian digital sphere.

Evidence-based policymaking stands at the forefront of contemporary governance, where data and evidence have emerged as indispensable allies in shaping effective and informed decisions. This article embarks on a comprehensive exploration of the challenges and critical issues encountered when data assumes the role of evidence in policy formulation. The foundation of this investigation is rooted in the extensive body of literature on evidence-based policy-making. We delve into the scholarly discourse, tracing the evolution of policy formulation from relying on intuition to being guided by empirical insights. As we navigate through this intellectual landscape, the crucial role of data as a catalyst for this transformation becomes apparent. Delving deeper, we will explore the intricacies of data and the rise of big data. Once regarded as mere numbers, data now represents the currency of the information age. Its volume, velocity, and variety characterize it, making it a powerful tool for generating evidence and formulating policies. As we explore its features, we uncover the potential of data to unlock unprecedented insights and inform governance with empirical precision. To conduct a comprehensive examination of the difficulties encountered when utilizing data as evidence in policy-making, we employ a rigorous scoping review methodology. Through meticulous screening, we have identified and analyzed 36 exemplary articles that offer invaluable insights into the multifaceted landscape of data-driven governance. These articles provide a comprehensive overview of the challenges, which can be grouped into three distinct clusters: technical challenges arising from data complexities, legal and privacy dilemmas intertwined with governance, and the formidable issues faced by policymakers. Our discussion unravels the intricate web of challenges, ranging from data quality and integration to confidentiality, ethics, and governance issues. We delve into the intricacies of data access, the fight against bias, and the challenges posed by data volume and complexity. Simultaneously, we explore the complex legal landscape of data ownership, security, sharing, and compliance. The challenges policymakers face in fostering data-driven cultures, navigating resource constraints, and communicating data-driven insights are brought to the forefront. In conclusion, our exploration sheds light on the complex challenges and crucial issues that underlie the use of data as evidence in evidence-based policy-making. This research underscores the transformative power of data in governance and emphasizes the challenges and pressing issues associated with using data as evidence in policymaking.