The Microfoundations of Entrepreneurial Cognition Research: Toward an Integrative Approach
Bibliographic record
Abstract
In this monograph, we adopt a microfoundations-type approach to understanding the present state of the field of entrepreneurial cognition research. The notion of microfoundations - which link micro concepts to macro concepts [Barney and Felin, 2013] - is increasingly being utilized to unbundle compound processes, and thereby to generate improved explanations in social science research. From its roots in psychology, we selectively review and trace the progress of the field of entrepreneurial cognition research over time, and we make a case for socially situated cognition as a new and useful framework in which the microfoundations of some of the emerging and more dynamic approaches to the study of entrepreneurs' thinking can be understood and organized. We also outline some productive directions for future entrepreneurial cognition research. We believe that the review of these earlier roots enables the reader to more fully appreciate how the development of social cognition research intertwines with other fields in influencing the current state of entrepreneurial cognition research.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".