Inequalities in Firms’ Access to Credit in Latin America
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A variety of social and economic institutions have contributed to the decline in poverty and inequality in Latin America. We focus on the bank-SME nexus because of the importance of banks as a source of finance for small and medium enterprises (SMEs), and the potential role that SMEs can play as sources of innovation, employment, and in reducing poverty and inequality. Our regression analysis of data from World Bank (WB) surveys of firms in Argentina, Brazil, Chile, and Mexico shows that firms that are smaller, newer, less technically advanced, and less well-located firms are more likely to report being credit constrained. The factors that did not count are executive characteristics such as gender, education, and experience in the sector, and firm performance or foreign ownership. Firms that worked with several banks, developed affiliations to business groups or were in trade and political associations were less likely to report credit constraint.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it