Interprofessional Education: A Basic Need of Healthcare Department in Pakistan
Bibliographic record
Abstract
Inter professional education (IPE) is the core concept of healthcare department in most of the developed countries on both student and professional level. There is no objection on its necessity. Top ranking universities of the world, especially of developed countries are working on IPE. But some of developing countries like Pakistan are almost unaware of this concept. No one is having the basic concept of IPE, except few, and they are not practicing in IPE so far. Talking about Punjab, there is no awareness for the concept of IPE. It is the need of our healthcare department that we must introduce IPE to improve healthcare quality. This survey was conducted to check the readiness for IPE among pharm D and MBBS students in different institutes of medicine and pharmacy of Lahore. Team went to different pharmacy and medical colleges and asked the students to fill in a questionnaire having 19 items, which was rated by the students on Likert scale. The result shows a conflict in the opinion of pharmacy and medical students. Team also interviewed the respondents shortly. This interview showed many reasons explained by medical students for their response but the most prominent one was the superiority complex. The need of the hour is to introduce IPE in universities for changing the attitude of medical students towards IPE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".