Biodiversity regulation and green innovation: evaluating the porter effect
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
Abstract We demonstrate that corporate green innovation undergoes a structural transformation under China’s Green Shield Program (GSP), a biodiversity conservation initiative integrating super-hierarchical supervision with multi-party co-governance. Using quasi-experimental evidence from difference-in-differences estimation, our analysis reveals that the GSP significantly enhances corporate green innovation performance and generates spatial spillover effects across nature reserves of different administrative levels, thereby compensating for the inherent limitations of conventional environmental regulation. Dynamic effects demonstrate that firms shift from passive, strategic innovation in the early stages to active, substantive innovation later on. Mechanism tests identify three transmission channels: improved environmental information disclosure, increased ecological awareness among management and reduced agency costs. Heterogeneity analysis indicates stronger effects in state-owned enterprises and industries with limited market competition. Our findings enrich the environmental decentralization theory through biodiversity policy applications and support the Porter hypothesis with practical implications for implementing the Kunming-Montreal Global Biodiversity Framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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