Taking Stock and Moving Forward: Independence of Entrepreneurship as a Discipline and the Intellectual Structure of Entrepreneurship Research in Strategy Venue
Bibliographic record
Abstract
Entrepreneurship has grown into a full-fledged, vibrant discipline, not only drawing on but also spawning a spectrum of research streams with various theoretical perspectives and empirical evidence. However, strategy journals had traditionally been home to many earlier entrepreneurship research insights. How has the intellectual structure of the entrepreneurship research published in strategic outlets evolved, given the disciplinary maturity of entrepreneurship? To answer this question, we performed a visual bibliometric analysis on the full archive of 25 years’ research on entrepreneurship published in a leading strategy journal. Our results uncover the intellectual development trajectory around entrepreneurship research targeted at strategy venue, and reveal the key elements such as research methods, level of analysis, variables, and correlations about such a body of research. This study provides an important starting point for reflecting on the particularities of boundary-crossing entrepreneurship research, and for identifying further avenues of theoretical and empirical inquiries.
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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 | 0.019 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".