Expanding horizons, shrinking habitats: Firm scope and biodiversity risk
Bibliographic record
Abstract
• Our findings reveal a significant positive relationship between firm scope and biodiversity risk, indicating that firms operating across broader product markets face greater ecological vulnerabilities. • This relationship weakens in firms with strong corporate culture and high operational efficiency, while it intensifies in environmentally sensitive industries and those with greater analyst coverage. • These findings enrich the literature by highlighting how corporate diversification strategies can exacerbate ecological risks. • The study provides practical implications for managers and policymakers, underscoring the urgency of embedding environmental considerations into strategic planning to mitigate biodiversity risks. Biodiversity risk represents a pressing global challenge with far-reaching consequences for ecosystems, economic stability, and corporate sustainability. This study explores the link between firm scope—the breadth of related product markets a firm engages in—and biodiversity risk, leveraging a comprehensive dataset of U.S. publicly listed firms. Our findings reveal a significant positive relationship between firm scope and biodiversity risk, indicating that firms operating across broader product markets face greater ecological vulnerabilities. However, this relationship weakens in firms with strong corporate culture and high operational efficiency, while it intensifies in environmentally sensitive industries and those with greater analyst coverage. These findings enrich the literature by highlighting how corporate diversification strategies can exacerbate ecological risks. The study provides practical implications for managers and policymakers, underscoring the urgency of embedding environmental considerations into strategic planning to mitigate biodiversity risks.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".