Interest in research among the undergraduate students of medical and dental colleges of Pakistan.
Bibliographic record
Abstract
Objectives: The aim of this study was to find the interest in research among the undergraduate students of medical and dental colleges of Pakistan. Study Design: Cross-sectional study. Setting: Amongst the students of four medical institutes. Period: April to May 2018. Material & Methods: Sample size was 500 of undergraduate MBBS and BDS students from 1st year to final year. Participants were given a questionnaire and responses were analyzed with SPSS software version 21. Results: The mean age of participants was 23.24 +/- 1.85 years. Female students were more (63%) as compared to male students (37%). Seventy percent (70%) students were interested in different research work and more than 85% students were interested to continue their future career in academics. Participants were more interested in practical training as compared to research and theory. Most of the students were interested to carry out research in clinical field as compared to non-clinical field. The knowledge of research methodology was more in senior students. Student’s knowledge about “impact factor of journal” was low. Conclusion: In this research it has been found that a good number of participants were interested in research activities so measures should be taken to facilitate and motivate them by giving some sort of award to the researchers to increase the publications from Pakistan. Easy access to internet facilities must be provided to promote research activities. Efforts should be made to find out reasons why some students consider research less important. It is also need of the day to develop culture of research by senior faculty members of academic institutes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".