Secrets of Gazelles: The Differences between High-Growth and Low-Growth Business Owned by African American Entrepreneurs
Bibliographic record
Abstract
The research findings are based on a national survey of 350 African American business owners whose companies had ten to one hundred employees. Each quarter of 2002 and 2003, owners were randomly selected and interviewed. Companies were classified into three groups according to their annual employment growth over five years: gazelles (20 percent or greater rate of growth), growth-oriented firms (1 to 19 percent), and no-growth firms (less than 1 percent or negative). In comparison to no-growth firms, gazelles were more likely to market to the government sector, less likely to compete on the basis of price, more likely to serve regional and national markets, and more likely to have fewer African Americans workers. CEOs of no-growth companies were more likely to have entered business because they lost a previous job. Surprisingly, no statistically significant differences appeared in thirty-nine other variables that defined owner attributes, firm characteristics, and business strategies of gazelles and no-growth firms.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".