Research Performance at Indian Institute of Management Sirmaur: A Five-Year Bibliometric Review
Bibliographic record
Abstract
This study aimed to evaluate the research productivity of the Indian Institute of Management Sirmaur, Himachal Pradesh, from 2019 to 2023. The study analysed 186 publications from the Scopus database using Bibliometrix and Biblioshiny of R Studio. The results showed a remarkable growth in research output, with a compound annual growth rate of 112.99%, which increased the output from 4 to 85 publications. The majority of this output consisted of articles (83.87%), indicating the institute’s preference for traditional scholarly communication. Business, management, and accounting emerged as the primary focus areas, reflecting the institute’s core academic strengths. The analysis also identified significant international collaborations, particularly with Canada, the USA, and Saudi Arabia, highlighting a broadened global research impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.034 | 0.035 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".