This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 1–4 of 4 papers
(著者不明)
This report reveals that global finance flows remain heavily skewed toward nature-negative activities, with US$7.3 trillion harmful vs US$220 billion for Nature-based Solutions in 2023. It calls for a 2.5x increase in NbS investment to US$5…
Correia-Pinto, Patrícia, Castro, Antonio J., Rebelo, Hugo +1
This harmonized dataset compiles 1,798 nature-related indicators from 25 business and policy initiatives, aligned with SEEA-EA, EBVs, and EESVs. It includes metadata on type, thematic scope, spatial scale, and confidence level, supporting i…
Miyuki Nagai
This study develops a scoring framework to evaluate biodiversity practices of clean beauty brands, comparing 10 international and Japanese brands. Findings show that biodiversity performance depends more on governance mechanisms (e.g., thir…
(著者不明)
This paper examines the relationship between firms' biodiversity-related disclosures and stock returns and idiosyncratic risk, providing empirical evidence on how greenwashing concerns affect market valuations and investor perception.
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