214 apply only to selected operations rather than entire corporate groups. These structural features complicate the identification of appropriate units of analysis and the attribution of observed changes to VSS participation. In addition to institutional complexity, informational constraints further limit measurement. Data on participating entities are not always publicly available, consistently structured, or directly comparable across companies or external databases. Variations in reporting formats and disclosure practices create additional barriers to systematic evaluation. Building on the proposed definition and measurement framework, the paper applies this approach to the case of the RMI, which runs widely adopted standards operating at a critical supply chain pinch point. This case illustrates both the feasibility and the limitations of assessing effectiveness under real-world settings. 2. CASE STUDY: RESPONSIBLE MINERALS INITIATIVE 2.1 Data and Methods The primary dataset for this study is the RMI Public List, which includes more than 400 active and conformant smelters and refiners across multiple metals, including gold, cobalt, tin, tantalum, tungsten, nickel, and others (see Figure 1). The dataset provides facility-level information such as country and whether a facility is subject to ESG assessment or crossrecognition under other standards. To examine institutional structures, facility-level records are supplemented with firmlevel ownership data from LSEG. For each facility, ownership is identified at two levels: the immediate operating entity and the ultimate parent company. Both are classified as publicly listed, privately held, or government-owned. This two-tier classification reflects the layered organizational configurations in which RMI-assessed facilities are embedded. The analytical approach is descriptive in nature. It does not estimate causal effects of assessment. Rather, it examines how structural concentration, cross-recognition arrangements, and ownership heterogeneity shape the institutional and informational conditions under which effectiveness could be evaluated. 2.2 Results 2.2.1 Structural Concentration of Midstream Facilities The distribution of RMI facilities across metals and supply chain levels is shown in Figure 1. Gold accounts for the largest number of active and conformant facilities at the pinch point level, followed by cobalt and tin. Together, these metals represent the majority of facilities in the dataset. Other metals, including tantalum, nickel, tungsten, and copper, are represented in smaller numbers.
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