Entrepreneurship and Innovation at the Base of the Pyramid: A Recipe for Inclusive Growth or Social Exclusion?
Bibliographic record
Abstract
abstract Policy makers often see entrepreneurship as a panacea for inclusive growth in underdeveloped ‘Base of the Pyramid’ (BOP) regions, but it may also lead to unanticipated negative outcomes such as crime and social exclusion. Our objective is to improve the understanding of how entrepreneurship policies can lead to socially inclusive growth at the BOP. Drawing on data collected from Brazilian tourism destinations with varying entrepreneurship, innovation, and social inclusion policies, we argue that weak institutions coupled with alert entrepreneurs encourage destructive outcomes, especially if entrepreneurship policies are based solely on economic indicators. Policies addressing both economic and social perspectives may foster more productive entrepreneurial outcomes, albeit at a more constrained economic pace. The study extends the related BOP, entrepreneurship, global value chain, and sustainable tourism literatures by examining the poor as entrepreneurs, the role of local innovation, and how entrepreneurship policies generate different social impacts within poor communities.
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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 | 0.003 | 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 | 0.013 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".