Interdisciplinary Approach: A Lever to Business Innovation
Bibliographic record
Abstract
The advances in interdisciplinary studies are driving universities to utilize their available resources to efficiently enable development processes and provide increasing examples of research while gradually allocating the disciplines’ resources. Ultimately, this trend asks universities to provide a platform of integrated disciplines, along with solid management to support the full-life cycle of interdisciplinary studies in fulfillment with internal policy and external regulations. To achieve this, we believe that this trend matches with business scholars to make a meaningful effort to show that their research thinking is interdisciplinary in nature. The key question is how business scholars, as professionals, provide the most value from academic disciplines in interdisciplinary research to solve real-life problems. Answering this question is accomplished in this study by using theoretical analysis to explore the concepts, benefits and uses of the existing knowledge base in interdisciplinary research as an innovative approach that links the business related-disciplines, people, and places involved to allocate universities’ resources effectively.
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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 | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.007 | 0.043 |
| Scholarly communication | 0.024 | 0.027 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".