الفصل الأول: أشعار نازك الملائكة وبروين شاکر(المتشابهة)
سأتناول في ھذا الفصل بعض أشعار نازك الملائکۃ وبروین شاکر ثم سأتحدث عن المتشابھات في بعض أبیاتھما بشکل أجمالي، واتضح لي من خلال عملي ھذا أن ھناک متشابھات فیما بینھما (نازك الملائکۃ وبروین شاکر) مع أن واحدۃ منهما عربیۃ والثانیۃ غیر عربیۃ، فمن خلال بحثي استنتجت بأنھما من الشاعرات الجدیدات لذلك ھُناک تشابہ في عصرھما وأحوالھما السیاسیۃ والدینیۃ والعلمیۃ والإجتماعیۃ وجمیع ھذہ المؤثرات لھا الدور الکبیر في تکوین الأفکار والأسالیب المتشابھة مع بعضھما البعض وأنھما من مشجعي الشعر الحر وصدق التعبیر لہ الید الأکبر في إیضاح أفکارھما وإیصال المعنیٰ الصحیح إلی القاريء أو السامع۔
وقد أخذت قصیدۃ من نازک الملائکۃ وقصیدۃ من بروین شاکر وقمت بمقارنتھما، ووضعت أسماء من خیالي لکل قصیدتین (قصیدۃ لنازك الملائکۃ وقصیدۃ لبروین شاکر) وھکذا۔
جدول القصائد المتشابهة
اسم قصیدۃ بروین شاکر أو بیت من غزلھا
اسم قصیدۃ نازك الملائکۃ
الإسم الخیالي
المبحث
کیسی بے چہرہ رُتیں آئیں وطن میں اب کے
Religion is considered as an integral part of individuals’ daily routine practices in the society. People perform religious obligations very rigorously and avoid all the religiously declared prohibited acts. This current study aims, to identify the role of group conformity towards adopting sectarian identities by individuals with the emphasis of exploring the practices of sectarian identities that causes an environment of inter-group disintegration in the community. This study will be significant in recommending initiatives that can create an environment of harmony between people belonging to different sectarian believers. Qualitative research method was applied to analyze group conformity and individuals’ behavior towards practicing sectarian identities. Population was based on rural setup of Manddi Faiẓ Abad. Twelve participants were selected through purposive sampling technique. Structured interview guide was used as data collection tool and themes was extracted to describe existing trends and patterns regarding group conformity and sectarian identity construction. Results revealed efficacious role of group conformity to encourage individuals towards adopting and practicing any particular sectarian identity in the society. Results highlighted that, desire of getting religious hegemony and supremacy with the courtesy of group conformity that make individuals intolerant on sectarian grounds and creates an environment of disintegration in the society. Sectarian difference not only creates religious
An important problem in Multilevel Modeling (MLM) is to find sufficient sample size for accurate estimation purposes. In MLM apart from the general factors of sample size estimation i.e. the test size, the effect size, SE (standard error) of the effect size and power of the test, additional factors like, magnitude of the ICC (Intra Class Correlation), total number of clusters, the number of parameters to be estimated, and the information whether the design is balanced or unbalanced may play a significant role. In this study, the significance of these factors in the context of MLMs is evaluated and their mutual relationship is explored through simulation study. It is found that little problem will arise in estimation of sample size for fitting multi-level model if standardized effect size δ is 0.2 or lower and intra-class correlation ρ is also low (0.05 or less), here substantial power (0.80) can be achieved when J (Number of clusters) is 50 or more. A small upward shift in the ρ (0.1), causes alarming increase in the total number of clusters to be sampled. Secondly, it is observed that the number of clusters to be sampled is playing a greater role in power enhancement as compared to cluster size. Thirdly, significant changes in the power of estimation are observed when the effect size δ increases from 0.2 to 0.4. Fourthly, the level II covariate (with R2= 0.3, 0.6) if added in the model in the model it can significantly increase power of the multilevel models even in the presence of small number of clusters. Two methods of estimation commonly used for multilevel modeling, IGLS (Iterative Generalized Least Square Method) and MCMC (Monte Carlo Markov Chain) are compared with variety of models using limited and extended simulations. The study reveals that the MCMC estimates for the fixed effect is superior to its counterpart IGLS on all the three grounds i.e. unbiasedness, efficiency, and the proportion of the true value captured by the confidence interval/credible interval. As far as estimation of the random effect is concerned, MCMC is better on the proportion of the true value covered, however, IGLS gain considerable lead on the unbiased and efficiency criterion. Further, it is observed that MCMC respond more positively to the extended simulations as compared to IGLS.