Abstract
<p>This article proposes a seven-layer organizational frame for online-only research on the digital class in state-entangled digital states — contexts in which conventional methods (interviews, representative surveys, labor-market statistics) are either unavailable or systematically biased, and where the sectoral optics of “IT firms plus workers” cannot hold the simultaneous weight of state, regulatory, investment, educational, symbolic-mediation, and civic-audit layers. Conceptually, the article proposes a shift from “sector” to “access-conversion ecosystem”: technical capital is converted into product, infrastructural, financial, educational, symbolic, and accountability resources through seven conversion functions (L1–L7). Methodologically, it proposes an online-only sampling frame with an evidence-ladder discipline (SRC/TRC/EVD/LNK/SNP/AMB registers and EV_STRONG/CONF_3 grades) and an explicitly tagged bias-correction supplement that turns visibility bias from a methodological limitation into a coded variable and a diagnostic instrument for the sociology of online visibility. The Kazakhstan case (Pilot 1: 150 core organizations across the seven layers, with 30 bias-correction supplement candidates) reveals four structural observations: the production core is less directly observable than its public periphery; gatekeeping (L4) is asymmetrically centralized; the education pipeline (L5) operates as a promise machine with a gap between the visibility of promise and the visibility of outcome; symbolic mediation (L6) and civic audit (L7) function as independent capitals, irreducible to “industry plus context”. The “visibility ≠ influence” discipline emerges not as a methodological caveat but as substantive defense of mapped actors against the forms of political miscodification typical of state-entangled contexts. The instrument is applicable to parallel digital states with active ecosystem policy and a developed public-visibility infrastructure.</p>