Different paths to the same Business: A Micro-level view of Entrepreneuring via Replication
Bibliographic record
Abstract
Entrepreneurship research has traditionally focused on far-from- equilibrium economic processes. Through doing so, significant insight have been made into the nature of innovative discovery and creation opportunities. However, this focus led to unintentional neglect of near-equilibrium entrepreneurship – entrepreneurship happening in established markets, where participants mainly replicate existing ventures to add supply to existing markets, often because no other employment opportunities are available. Moreover, when researchers do engage with the phenomenon, it tends to be at a macro-level stressing the institutional drivers of homogeneity. However, there is ample reason to believe this is an oversimplification of a complex phenomenon. As such, we undertook a 33-month qualitative study in Koforidua, Ghana. We found six distinct pathways through which replication occurs, and that use of these pathways is guided by entrepreneurs’ knowledge and financial constraints. More than this, we find that entrepreneuring enables the dynamic accumulation of knowledge and resources, allowing entrepreneurs to progressively relax constraints and to undertake more agentic venture selection processes.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.053 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".