Knowledge Architecture:ConceptsObservationsEvidence

Computational Access Gap (CAG)

CAG

Gap Between Potential and Actual Computational Access to Entities

Proposed hypothesis — not yet testedpublished

CAG measures the gap between potential and actual computational access.

July 12, 2026
Version 1.0
5 min read
By Marco Patrone
cagaccess_gapcomputational_accesstransmission_metricremediation_opportunity

Definition

CAG measures the gap between what computational access is potentially possible for an entity and what is actually realized. Higher CAG indicates unrealized allocative potential.

CAG assesses unrealized allocative potential—the gap between what computational access is possible and what is actually achieved.

Conceptual Formula

CAG(e) = potential_access - actual_access, normalized by potential.

Methodology

Type

index construction

Data Sources

synthetic

Confidence Level

low

Description

CAG(e) = potential_access - actual_access, normalized by potential.

Limitations

  • Potential access is theoretical
  • Actual access measurement is proxy

Key Takeaways

Key Points

  • CAG scales 0-1
  • Higher indicates unrealized potential
  • Remediation opportunity indicator

Target Audience

firmsinfrastructure providers

Relevance Tags

cagaccess_gapcomputational_accesstransmission_metric

Source Paper

The Zero-Click Economy

HomeSelf Research (2026)

View on Zenodo
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Citation

For the Computational Access Gap (CAG), see HomeSelf Research (2026), The Zero-Click Economy.

DOI: 10.5281/zenodo.21321629

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