مطالب

Mounting attention has recently been paid to authorial stance in academic writing due to its important role in the interpersonal aspect of writing, encompassing the ways in which authors establish connections, convey attitudes, and engage with an audience. This study was an attempt to explore how native and non-native authors of Applied Linguistics deploy linguistic features to project their authorial stance. To this end, a corpus of 100 research articles authored by native and non-native researchers was collected from journals in the field of ELT. Hyland's Interpersonal Model of Metadiscourse (2005) was employed to differentiate the features produced and figure out how authors navigate the complexities of expressing their meaning while considering the ELT community expectations, and SPSS was used to analyze the data. Based on the results, the proportion of interactive resources was found to surpass that of interactional resources in both native and non-native writings, with transitions being the leading feature, followed by evidentials; and regarding the interactional resources, boosters, and hedges were the most dominant features employed by native and non-native authors, respectively. Overall, no tendency was found towards textuality through which authors consider the target audience (engagement markers), signal their confidence through the portrayal of authors' feelings (attitude markers), and take credit for their findings (self-mentions) throughout the whole corpus, particularly non-native writings. It seems that writing courses offered in non-native contexts require improvements to meet the standards of academic writing. Therefore, the study has important implications for both non-native and novice researchers and course designers.

The purpose of this study was to compare the functioning of five restrictive CDMs, including DINA, DINO, A-CDM, LLM, and RRUM, against the G-DINA model to identify the best-fitting CDM which can better explain the interaction underlying the attributes of the reading comprehension section of an Iranian high-stakes language proficiency test. To achieve this aim, item responses of 1152 examinees to the items of the test were examined. The six CDMs were initially compared in terms of relative and absolute fit statistics at test-level to choose the best model. It was found that the G-DINA model outperformed compared to the restrictive models; thus, it was selected for the second phase of the study. Concerning the second purpose of the study, the G-DINA was used to identify strengths and weaknesses of the examinees. The results revealed that making an inference and vocabulary are the hardest attributes for examinees of the test, and understanding the specific information is the easiest attribute. Finally, the models were also compared at item-level. The presence of a combination of L2 reading attributes was found.

EXTENDED ABSTRACT INTRODUCTION The number of revealed corruption-related crimes is one of the major challenges of Iran which has been significantly increased in recent years. According to official reports, although only two cases of embezzlement were reported in 1990s and 2000s with a total value up to $ 800 million, administrative corruption has significantly increased in 2010s with 13 large corruption cases and a total value up to $ 14 billion and a growth of over 1500% compared to 1990s and 2000s (The Iranian Students News Agency[1] (ISNA), 2017). The spread of such amount of corruption in administrative and bureaucratic system of the country can have irreparable economic and social consequences. The statistic investigations have shown that macroeconomic indicators including economic growth, employment, unemployment, poverty, inflation and income distribution have become less favorable in 2010 compared to previous decades (Statistical Center of Iran, Iran Statistical Yearbook, 2017). In this regard, the following questions can be raised: is there a relationship between corruption and the indicators of income distribution and poverty in the country? Since the volume of international and unilateral sanctions on Iran has increased in the 2010s, does such a widespread growth in the volume and value of corruption cases in Iran have a relationship with sanctions?   METHODOLOGY Therefore, the purpose of the present study is to investigate the effect of sanctions on causal relationship between corruption, income inequality and poverty in Iran during 1984 to 2020. For this purpose, the indices of per capita income, poverty line, administrative corruption and control of corruption, Atkinson and Gini have been utilized to investigate their interactions through Toda-Yamamoto Causality Test.   FINDINGS Findings of research show that:   sanctions have affected the causality of per capita income on administrative corruption. sanctions have affected the causality of corruption control on per capita income. sanctions have affected the causality of income distribution on per capita income. sanctions had no effect on causality of per capita income, on Atkinson Index and vice versa. sanctions had no effect on causality of per between poverty line, on administrative corruption and vice versa. sanctions had an effect on causality of per between poverty line, on corruption control and vice versa. sanctions had a significant positive effect on poverty line, but had no significant effect on GINI index. In other words, sanctions have affected the causality of income distribution on poverty line. sanctions had no effect on causality of poverty line, on Atkinson Index and vice versa. sanctions had no effect on causality of GINI index, on administrative corruption and vice versa. sanctions had no effect on causality of GINI index, on corruption control and vice versa. sanctions had a significant positive effect on administrative corruption, but had no significant effect on Atkinson index. In other words, sanctions have affected the causality of income distribution on administrative corruption. sanctions had a significant positive effect on Atkinson index, but had no significant effect on corruption control. In other words, sanctions have affected the causality of corruption control on income distribution.     CONCLUSION The purpose of the present study was to investigate the effect of sanctions on causal relationship between corruption, income inequality and poverty in Iran during1984 to 2020. For this purpose, the indices of per capita income p, poverty line, Atkinson, GINI, administrative corruption and corruption control were investigated. In general, the following results were obtained from the present study:   Income distribution is not an effective variable for poverty in Iran. Corruption is an effective variable for causality of poverty in Iran and its significance level is higher under sanctions condition. Corruption and poverty cannot properly explain the income distribution in Iran. However, the corruption control can be the cause of income distribution and poverty line is a proper representative for the cause of income distribution under sanctions conditions. Income distribution is a strong variable for causality of corruption in Iran. Poverty can properly explain the causality of corruption in Iran under sanctions condition, but is not the cause of corruption under normal condition.   According to the obtained results, it seems that sanctions condition is an effective variable for the relationship between variables of income distribution, corruption and poverty. However, the effective factors of income distribution need further investigations in future.