Notice bibliographique
Résumé
Academic Research on Urdu Language and Literature started much before creation of Pakistan, but there were very few who excelled to the level of PhD. Although there was no shortage of topics but researchers, academicians and universities offering PhDs were rare. Even Pakistan’s oldest University of Punjab established department of Urdu in 1948, Karachi University followed couple of years later. For the first 20-25 years of Pakistan not much could be achieved in field of credible research on Urdu. \n \nIt only improved in 1973 when Dr. Waheed Qureshi took charge of Urdu department, Punjab University. He opened new doors for research relating activities, engaged and supported researchers in there work, which gave tremendous boost to academic research on Urdu. His predecessors Dr. Ghulam Hussain, Dr. Khwaja Muhammad Zakria and Dr. Sohail Ahmad Khan had the same generous attitude towards research. In my tenure as head of Urdu Department (2000-2001), regular PhD program was initiated in parallel to already existed Private PhD program, greatly increasing number of PhD students. At the same time Allama Iqbal Open University, Universities of Karachi, Sindh, Multan and Bhawalpur had there own M.Phil and PhD programs. Research on Urdu Language and Literature is not confined to universities in Pakistan. Research work on Urdu is carried out globally. Universities in USA, Canada, UK, France, Belgium, Turkey, Bangladesh and specially India are awarding M. Phil and PhD degrees in Urdu. \n \nNeed for Comprehensive List of Topics \n \nThough the advancement and expansion on research on Urdu is encouraging but there are also some points to ponder about such as lack of coordination between Urdu departments of universities. No university has any idea of topics others are working on or have been researched, nor there is any elaborated and comprehensive list of topics available one can consult before assigning a topic to researchers resulting in repetition of topics. One can find multiple research papers on one topic, of which many might be from same university. This is sheer wastage of time, resources and expertise. \n \nAnother disadvantage of non availability of a comprehensive list is that research trends can not be judged, which hinders search for new topics. \n \nMy association with academic research is spread over 40 years and I am affiliated with M.A, M. Phil, and PhD level research work being done in Punjab and Allama Iqbal Open universities. It was always difficult to confirm if any previous work is available on a topic, at times after putting months of work on a topic one gets the knowledge that some university had already researched on the topic or has assigned the topic for research. \n \nDue to above mentioned reasons, need for a comprehensive list of topics is evident. I over the years kept notes on credible research work done, using my notes and other available documents complied this list.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,022 | 0,006 |
| Communication savante | 0,013 | 0,008 |
| Science ouverte | 0,002 | 0,011 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,042 | 0,010 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».