COUNTER-CLAIMING FOR A CRIME NARRATIVE: AN EVALUATION OF THE DEFENDANT’S PLEA AT THE CORRUPTION CRIMINAL COURT

In a criminal trial, the plea of the accused is arguably a very important appraising discourse tool functioning mainly to counter the crime narrative made by public prosecutors in their indictment and closing statement. As an appraisal instrument, the plea represents the stance of the accused with regards to the facts of the case as well as the legal aspects of the alleged crime. In this regard, the plea may serve both argumentative and persuasive functions and may shape, to some extent, the understanding and the consideration of the judges who decide on the case. The study, which is qualitative in nature, uses Martin and White’s appraisal theory (Martin and White, 2005) to investigate evaluation strategies employed by an accused of a corruption case in his plea. Evaluation strategies are defined here as strategies in discourse used to counter the crime narrative by employing relevant evaluative resources. The result of the analysis shows that the accused strategically uses the three main discourse semantics resources, i.e. engagement, attitude, and graduation. The contractive options of engagement (deny, counter, and pronounce) are used to counter aspects of the crime narrative, while judgment of propriety (social sanction) and capacity (social esteem) of the attitude component are employed mainly to evaluate aspects of the crime narrative negatively and aspects of the counter narrative positively. Furthermore, amplification and quantification options of the graduation component are used to strengthen the degree of evaluation. It can be concluded that the narrative of plea is arguably an important evaluative instrument which, strategically and professionally constructed, may help the accused convince the judges of his/her innocence

Reducing family poverty through an Islamic women’s empowerment strategy in Indonesia: An analytical network process approach

This study is intended to develop a strategy for the socio-economic empowerment of women from low-income families based on an Islamic perspective. The research was motivated by Indonesia’s low score on the Gender Inequality Index (GII) compared to other countries, indicating the gap between men’s and women’s empowerment in Indonesia. The percentage of women who become the heads of poor households increases yearly. This qualitative study uses the Analytical Network Process (ANP) to test the social welfare measures for low-income families carried out by governments, Islamic philanthropic institutions, and Islamic microfinance institutions. As many as fifteen respondents involved in the ANP method were experts on the studied problems, namely regulators, practitioners, and academics. The research results indicate that the main priority issue developing women’s empowerment is the development of partnership networks. In the next stage, the experts concluded that business assistance and mental-spiritual development were the main priorities for empowering women and reducing family poverty. The provision of financial access is the last priority. One implication of this study is that the empowerment program for women from low-income families must be holistic, e.g., by forming a Group Lending Model (GLM) with a modification of the majlis ta'lim (Islamic community discussion group)

Book review

Natural Language Processing (NLP) is a 'theoretically motivated range of computational techniques for analyzing and representing naturally occurring texts at one or more levels of linguistic analysis for the purpose of achieving human-like language processing for a range of tasks or applications' (Liddy, 2001, p.1). NLP is an increasingly popular field of study nowadays. The applications of NLP are widespread. There are many applications made possible by NLP such as translation tools, speech recognition and transcription softwares, speech to text and text to speech applications, corpus tools, predictive text applications, and many more. These in return have contributed to the increase in the popularity of NLP itself, not only among academics but also among wider audiences who have benefited from it