The link between product diversification and performance among Spanish manufacturing firms: Analyzing the role of firm size
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This study sheds additional light on the product diversification‐performance relationship for firms in a country having recently attained an advanced economy status in our period of analysis. We assume there will be an inverted U‐shaped relationship and use a sample of small, medium, and large Spanish manufacturing firms between 1994 and 2008. Our findings provide solid support for this assumption, and are identical when the sample consists of small, medium, and large firms and of large firms alone. Our results also suggest that the larger the firm, the higher the optimal level of diversification. Panel data models are used to control for unobservable heterogeneity and potential endogeneity problems. Copyright © 2015 ASAC. Published by John Wiley & Sons, Ltd.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it