حدود کی تعداد
جرائم حدود کی تعداد کے سلسلے میں اہل علم میں اختلاف پایا جاتا ہے۔ ابن حجر عسقلانی کے نزدیک
" جَمْعُ حَدٍّ وَالْمَذْكُورُ فِيهِ هُنَا حَدُّ الزِّنَا وَالْخَمْرِ وَالسَّرِقَةِ وَقَدْ حَصَرَ بَعْضُ الْعُلَمَاءِ مَا قِيلَ بِوُجُوبِ الْحَدِّ بِهِ فِي سَبْعَةَ عَشَرَ شَيْئًا فَمِنَ الْمُتَّفَقِ عَلَيْهِ الرِّدَّةُ وَالْحِرَابَةُ مَا لَمْ يَتُبْ قَبْلَ الْقُدْرَةِ وَالزِّنَا وَالْقَذْفُ بِهِ وَشُرْبُ الْخَمْرِ سَوَاءٌ أَسَكِرَ أَمْ لَا وَالسَّرِقَةُ وَمِنَ الْمُخْتَلَفِ فِيهِ جَحْدُ الْعَارِيَةِ وَشُرْبُ مَا يُسْكِرُ كَثِيرُهُ مِنْ غَيْرِ الْخَمْرِ وَالْقَذْفُ بِغَيْرِ الزِّنَا وَالتَّعْرِيضُ بِالْقَذْفِ وَاللِّوَاطُ وَلَوْ بِمَنْ يَحِلُّ لَهُ نِكَاحُهَا وَإِتْيَانُ الْبَهِيمَةِ وَالسِّحَاقُ وَتَمْكِينُ الْمَرْأَةِ الْقِرْدَ وَغَيْرَهُ مِنَ الدَّوَابِّ مِنْ وَطْئِهَا وَالسِّحْرُ وَترك الصَّلَاة تكاسلا وَالْفطر فِي رَمَضَان وَهَذَا كُلُّهُ خَارِجٌ عَمَّا تُشْرَعُ فِيهِ الْمُقَاتَلَةُ كَمَا لَوْ تَرَكَ قَوْمٌ الزَّكَاةَ وَنَصَبُوا لِذَلِكَ الْحَرْبَ "64
"ابن حجر عسقلانی نے سترہ جرائم کو حدود میں شامل کیا ہے اور گیارہ جرائم کے متعلق اتفاق ظاہر کیا ہے کہ یہ حدود میں شامل ہیں جو کہ مند رجہ ذیل ہیں ۔ زنا ، قذف ، سرقہ ، بغاوت، شراب نوشی، ارتداد ، حرابہ، ترک صلوٰۃ ، ترک صوم، سحر اور وطی بہائم۔ "
علامہ کاسانی ؒکے مطابق حدود کی تعداد پانچ ہے، جو کہ مندرجہ ذیل ہیں:
"الْحُدُودُ خَمْسَةُ أَنْوَاعٍ حَدُّ السَّرِقَةِ وَحَدُّ الزِّنَا وَحَدُّ الشُّرْبِ وَحَدُّ السُّكْرِ وَحَدُّ الْقَذْفِ۔ "65
ابن قدامہ ؒ حدود کی تعداد سات کا ذکر کرتے ہوئے لکھتے ہیں
"الْحُدُودُ سبعۃأَنْوَاعٍ حَدُّ السَّرِقَةِ وَحَدُّ الزِّنَا وَحَدُّ الشُّرْبِ وَحَدُّ الْقَذْفِوَحَدُّ الحرابۃ وحد الردۃ وحد بغی۔ "66
عبدالقادر عودہ شہید ؒکے بقول حدود کی تعداد سات ہے ، جو کہ یہ ہیں:
"جرائم الحدود معینۃ ومحددۃ العدد وھی سبع جرائم حَدُّ الزِّنَا وَحَدُّ السُّكْرِ وَحَدُّ الْقَذْفِ حَدُّ السَّرِقَةِوَحَدُّ الحرابۃ وحد ارتداد وحد بغی "67
جسٹس تنزیل الرحمن کے مطابق حدود اللہ کی تعداد چھ ہے
"حَدُّ الزِّنَا وَحَدُّ الْقَذْفِ وَحَدُّ الشُّرْبِ حَدُّ السَّرِقَةِ وَحَدُّ الحرابۃوحد الردۃ۔...
The study investigated the relationship of the multiple intelligences of the Bachelor of Secondary Education students and their teachers in their major subjects. Four hundred eighty-five (485) BSED students and twenty-two (22) teachers in their respective major subjects participated. The result demonstrates statistically significant in the multiple intelligences of the Bachelors of Secondary Education Major in Technology and Livelihood Education and Music, Arts, Physical Education and Health and their teachers in their respective major subjects. However, result also demonstrates no significance in the multiple intelligences of the Bachelors of Secondary Education Major in Filipino, English, and Mathematics and their teachers in their respective major subjects. The study shows that the dominant intelligences of the BSED students and their teachers in their major subjects are the interpersonal, intrapersonal, and their suited intelligences for their major subjects. The result evidently showed that the BSED students and their major teachers are people and self smart. This only shows that as a teacher, one should know how to socialize appropriately with others and have a deeper understanding with themselves. It also showed that the teachers are really smarter than their students in their major field of specialization. Educators must also consider the multiple intelligences of their students to fully develop their learning capabilities.
The World Wide Web and its millions of internet applications have revolutionized the way people to communicate, socialize, stay healthy, educate, conduct business, do politics, and do ?any-thing-at-all?. The huge amount of data generated by these applications is also proving quite valuable in the context of analyses, evaluations and predictions. These predictions help in organizational planning & management, to a very acceptable degree of accuracy. This research thesis is a study of several current researches on the extraction and analysis of short text messages or micro-blogs, from a social-science perspective. Specifically, this study investigates linguistic-frequency and sentiment analysis of micro-blogs in general, by identifying, collating and visualizing conversational and behavioral biases of people, from a very large twitter dataset of 6+ million tweets. This study explores short text analysis using freely available text processing and visual analysis tools. A novel contribution of this work is to investigate the effectiveness of automated labeling of tweets instead of manual labeling. Comparison of automatically labelled tweets with baseline STS-gold set. The baseline dataset of manually labelled twitter dataset show a very small deficiency of 6-8%, making our method viable for huge/big datasets. Main result of this study is a framework that encapsulates three current techniques for analyzing and visualizing microblogs. The frequency measurements and classification have been performed using the NLTK text processing tool. Sentiment Analysis has been carried out using NLTK and WEKA tools. Network Graphs made in Gephi software have been used to visualize user trends and behaviors, utilizing metrics from Networks Theory.