Entrepreneurship and the Face of Janus of Institutions: Stimulus Policies for High-Impact Entrepreneurs in Brazil and Russia
Bibliographic record
Abstract
Institutional theory has been widely applied to the study of entrepreneurship.Based on the current understanding of the institutional gap, we suggest that the relationship between formal institutions and entrepreneurship in emerging economies is reminiscent of the Face of Janus.Janus is a mythological figure with two faces, one looking backward and the other looking forward.Therefore, he is associated with transition and the chaos connected with the ambiguous relationship between the past and the future.This ambiguity may be seen as characteristic of entrepreneurship in emerging economies.In other words, the Face of Janus that looks backward corresponds to the institutional void, and the face that looks forward corresponds to stimulus policies that promote high-impact entrepreneurs.In this article, we comparatively discuss two case studies in Brazil and Russia.In Brazil, the Agency for Innovation's (Financiadora de Estudos e Projetos -FINEP) INOVAR program while in Russia the Skolkovo Foundation.This article contributes to the entrepreneurship literature by advancing the concept of the institutional void in the context of emerging economies and by identifying strategies to develop high-impact entrepreneurship in two countries that have received little attention in previous articles.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".