Interdisciplinary Approaches in Business Studies: Applications and Challenges
Bibliographic record
Abstract
Monodisciplinary research confines itself to expanding the literature, knowledge, and methodologies of a single discipline. In contrast, interdisciplinary studies adopt a holistic approach to solve current problems and create new knowledge informed by different disciplinary perspectives. While there are some debates and challenges regarding the position of interdisciplinary research within academia, interdisciplinary approaches have potential for creating new integrative research domains by combining various skill sets and expertise from various fields or disciplines to tackle critical problems across several areas, including in business studies. A particular application of interdisciplinary approaches will be discussed in connection with a larger research study. This research involves theories, literature, and methodologies from these practical and rapidly-changing fields: business studies, information systems, and consumer psychology.
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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 | 0.166 | 0.162 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.016 | 0.024 |
| Science and technology studies | 0.013 | 0.068 |
| Scholarly communication | 0.036 | 0.044 |
| Open science | 0.008 | 0.034 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".