BLOCK VECTOR Research Map

BLOCK VECTOR Research Map The BLOCK VECTOR Research Map is a visual guide to the Stable Authority Boundary (SAB), its formalization, core principles, applications, and related research. The collection examines a common systems problem: a machine, AI agent, autonomous system, or distributed system may remain technically capable of acting even when the authority, evidence, conditions, or information needed to justify that action have changed. Across the collection, this problem intersects with machine-readable provenance, dataset provenance, dataset integrity, metadata generation, data validation, automated transformation, computational reproducibility, derived datasets, tamper-evident data, persistent identifiers, and research data archives. These concepts matter wherever systems must establish not only what information is available, but where it came from, how it changed, whether it remains valid, and whether an action based on it is still authorized. FOUNDATION + FORMALIZATION Stable Authority Boundary (SAB) v1.0 — Conformance Specificationhttps://doi.org/10.5281/zenodo.21939806 Defines SAB and establishes assessable requirements for authority, evidence, refusal, degraded operation, bypass paths, reconstructible decisions, and deliberate non-action. SAB is directly relevant where execution depends on machine-readable provenance, dataset provenance, dataset integrity, data validation, or information produced through an automated transformation. A technically usable input or derived result does not by itself establish that the resulting action is authorized. CORE PRINCIPLE — AUTHORITY Authority Contraction and Refusal as Safety Invariants in Autonomous Systemshttps://doi.org/10.5281/zenodo.22009777 Explains why uncertainty and degraded conditions should contract operational authority rather than silently expand it. The same principle applies when evidence changes through an automated transformation, when the integrity of a source becomes uncertain, or when a derived dataset can no longer be tied confidently to valid source evidence. Refusal is treated as a positive safety property rather than a failure to perform. CORE PRINCIPLE — RESILIENCE Resilience Is Not Uptimehttps://doi.org/10.5281/zenodo.21995977 Distinguishes continuous operation from correct operation. True resilience preserves authority boundaries and produces evidence that remains reconstructible through degradation and recovery. In data-dependent systems, this includes maintaining dataset integrity, machine-readable provenance, data validation, tamper-evident data, and enough processing evidence to support computational reproducibility rather than simply keeping the system running. CORE PRINCIPLE — SILENCE Authority, Silence, and Failure Modes in AI-Driven Systemshttps://doi.org/10.5281/zenodo.22011497 Examines silence, non-response, and deliberate non-action as meaningful system outcomes. Missing input, incomplete metadata generation, failed data validation, uncertain provenance, or an inability to verify a transformed artifact may all require a governed decision not to act. Silence and refusal therefore become explicit system behavior rather than unexplained absence. CORE PRINCIPLE — EVIDENCE The Missing Layer: The Hidden Risk in Modern Autonomous Systemshttps://doi.org/10.5281/zenodo.21995175 Identifies the missing systems layer between technical capability and legitimate action. It emphasizes reconstructible decisions, provenance, and evidence that survive operational complexity. This includes knowing whether an input originated as an open research dataset, sample dataset, derived dataset, or other artifact; whether it has a persistent identifier such as a dataset DOI or data DOI; and whether its dataset provenance and transformation history remain available for independent examination. APPLICATION — INFRASTRUCTURE The Missing Boundary: The Unnamed Risk in Modern Infrastructurehttps://doi.org/10.5281/zenodo.22010565 Shows how critical infrastructure can remain technically capable while lacking an explicit boundary defining which actions remain authorized as conditions change. That problem increasingly intersects with dataset integrity, data validation, automated transformation, and provenance because infrastructure decisions may depend on data that has been aggregated, transformed, derived, or received from external systems. SYNTHESIS Authority, Refusal, and Resilience in Autonomous Systemshttps://doi.org/10.5281/zenodo.22100798 Integrates authority, refusal, silence, resilience, evidence, and testable conformance around the Stable Authority Boundary as a pre-execution design invariant. The synthesis provides the broader framework for understanding how authority decisions interact with machine-readable provenance, dataset provenance, computational reproducibility, automated transformation, derived datasets, validation evidence, and tamper-evident records across autonomous and distributed systems. READER GUIDANCE How to Read Zenodo Like a Systems Engineerhttps://doi.org/10.5281/zenodo.22102298 Presents a systems-engineering method for treating research repositories as technical signal surfaces. It is particularly relevant to research data archives, open research datasets, sample datasets, dataset DOI, data DOI, metadata generation, data processing examples, derived datasets, dataset provenance, dataset integrity, and computational reproducibility. The method uses repository terminology and adjacent search behavior to identify where technical attention is concentrated and where a solution may exist outside the vocabulary originally used to search for it. HOW TO USE THE MAP Start with the question that brought you here rather than reading the collection chronologically. Use the SAB Conformance Specification when the issue is formal authority or assessable behavior.Use the Authority work when conditions or evidence are changing.Use Resilience when continuity, recovery, or degradation is the problem.Use Silence and Refusal when correct behavior may require non-execution.Use the Evidence work when provenance, integrity, reconstruction, or reproducibility is central.Use How to Read Zenodo Like a Systems Engineer when the problem is discovering adjacent terminology, datasets, research activity, or unresolved technical seams. Interactive Research Map https://blockvectortech.com/publications/research-map.html Permanent Research Map Record https://doi.org/10.5281/zenodo.22102620 Author ORCID — David B. Forbes https://orcid.org/0009-0003-8833-3853