Systems Harm Analysis¶
Method — instantiates Structural Harm Mapping
Follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces.
A Systems Harm Analysis widens the frame past any single organization to the seams between institutions. It follows a person or group across the several agencies, programs, and systems whose individually defensible rules compound — waits stacked on waits, one program's requirement voiding another's benefit — into harm that no single institution owns or even sees. Its defining move is the interaction-and-accumulation lens: it asks not what each institution does but what the whole arrangement produces when its parts collide, and it isolates that compounding by asking what a person's trajectory would look like if the institutions did not run into each other.
Example¶
A returning-citizen program tries to understand why so many people are re-incarcerated within a year despite complying with every requirement handed to them. The analysis follows a single trajectory across institutions. Parole mandates a fixed home address — but housing programs exclude people with certain convictions. A steady job requires an occupational license — but the licensing board withholds it for that same conviction. Benefits lapse in the weeks between release and a first paycheck, while a supervision fee accrues the entire time. No agency is villainous; each rule is defensible alone. Their rules interlock into a trap. The counterfactual — the identical person if any one interlock were loosened — shows the harm lives in the combination. Illustratively, the cumulative burden peaks in the first sixty days, when every system's clock runs at once and a single missed step in one triggers failure in the others.
How it works¶
What distinguishes it is that its unit is a trajectory across systems, not a rule or an office:
- Follow the whole trajectory. Trace one person or group across every institution they must satisfy.
- Layer the burdens. Stack each system's demands over time to see the accumulation no single agency records.
- Find the interlocks. Locate where one system's rule cancels another's help — the compounding points that make the harm.
- Attribute by counterfactual. Compare the actual trajectory against one with an interlock removed, so the harm is pinned to the interaction rather than to any single part.
Tuning parameters¶
- System boundary — how many institutions you include. Too few misses the interlock; too many becomes unmappable.
- Trajectory unit — one representative journey or an aggregated cohort. The single journey is vivid; the cohort is defensible.
- Accumulation window — the time span over which burdens are summed, which decides whether you catch the crisis peak.
- Interlock focus — how hard you hunt for rules that cancel each other, the analysis's highest-value and hardest-won findings.
- Counterfactual construction — remove one interlock, or model a fully coordinated baseline. The stronger the counterfactual, the clearer the attribution.
When it helps, and when it misleads¶
Its strength is revealing harm that is invisible from inside any one agency and untouched by any single-agency reform, and pointing at the interlocks whose loosening would relieve the most. That is a search for leverage points, in Donella Meadows' sense — the few places where a change to the arrangement shifts the whole outcome.[1] Its failure mode is a map so sprawling that everything connects to everything and nothing is actionable — systems-thinking as an alibi. The classic misuse is invoking "it's the whole system" to excuse every institution from the fixable interlock it actually does own. The discipline is to converge on the handful of interlocks whose loosening most reduces the cumulative burden and to name which institution owns each, so the breadth ends in a short, owned list.
How it implements the components¶
cumulative_burden_layer— it sums how many separately-tolerable requirements stack, across systems and across time, into disabling harm no single office logs.counterfactual_comparison— it isolates the interaction's harm by comparing the actual trajectory against one with a single interlock removed.
It does not inspect one organization's internal rules and incentives — structural_pathway and harm_pattern_description are the Structural Audit's — nor start from the upstream social conditions of a population — affected_need_or_opportunity is Social Determinants Mapping's.
Related¶
- Instantiates: Structural Harm Mapping — it supplies the cross-institution view that exposes harm owned by no single agency.
- Sibling mechanisms: Structural Audit · Social Determinants Mapping · Access Pathway Map · Institutional Barrier Review · Policy Pathway Analysis · Equity Impact Assessment · Harm Reduction Dashboard · Remedy Co-Design Workshop · Affected-Party Review Panel
Editorial Notes¶
Form Classification¶
Form family: Analysis, Modeling & Optimization
Rationale: Systems Harm Analysis operates as an analytical, modeling, inference, comparison, or optimization procedure that derives insight or a solution because it follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces.
Independent corroboration: The frozen evidence defines Systems Harm Analysis as 'Follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces', so its operative form is Analysis, Modeling & Optimization.
Nearest alternative: Assessment, Review & Assurance — Systems Harm Analysis includes features of a bounded evaluation of existing evidence or work that produces a finding or disposition, but its defining operation is an analytical, modeling, inference, comparison, or optimization procedure that derives insight or a solution.
Review outcome: Independent reviewer agreement; medium confidence.
Origin Attribution¶
Primary origin: Sociology & Anthropology
Origin pattern: Cross-disciplinary synthesis
Present-day reach: Universal
Rationale: The defining operation is: Follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces. In the sociology_anthropology lineage, that operation is specifically evidenced by authoritative or primary work that requires mapping impacts across affected people, organizations, society, and interacting lifecycle contexts rather than examining a component alone. This makes sociology_anthropology the best historical origin, while the retained alternates document contributing methods and later applications rather than being mistaken for coequal origins.
Related originating lineages:
- Organizational & Management Science — organizational_management supplies a historically relevant parallel or contributing practice for the defining operation—Follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces—but the evidence does not make it the best primary lineage.
- Political Science — Political science and institutional power analysis supplies a parallel or contributing lineage for the mechanism's defining operation: follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces.
- Public Administration & Policy — Public administration, policy implementation, and program oversight supplies a parallel or contributing lineage for the mechanism's defining operation: follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces.
- Systems Thinking & Cybernetics — Systems science's feedback, stock-flow, boundary, and regulation tradition provides a formative adjacent lineage for the same systems harm analysis operation.
- Ethics of Technology & AI Governance — Technology ethics and ai governance supplies a parallel or contributing lineage for the mechanism's defining operation: follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces.
Review resolution: The blind reviewers disagree on primary lineage (organizational_management versus sociology_anthropology), so I adjudicated the mechanism rather than inheriting either label. The defining operation is: Follows a person or group across the several institutions whose separate rules compound into harm no single agency owns, and asks what the interaction — not any one part — produces. In the sociology_anthropology lineage, that operation is specifically evidenced by authoritative or primary work that requires mapping impacts across affected people, organizations, society, and interacting lifecycle contexts rather than examining a component alone. This makes sociology_anthropology the best historical origin, while the retained alternates document contributing methods and later applications rather than being mistaken for coequal origins. The cited NIST AI RMF Core directly supports the mechanism-specific operation and its disciplinary lineage. I retain all independently explained historical alternates without a numeric cap. origin_mode=cross_disciplinary_synthesis records how the mechanism arose; domain_reach=universal separately records how broadly it can now be applied.
Encyclopedia synthesis: The exact catalogued form synthesizes established practice rather than reproducing a single standard historical label.
Review outcome: Researched adjudication after independent review; high confidence.
Sources consulted:
References¶
[1] Leverage points — Donella Meadows' framework (Leverage Points: Places to Intervene in a System, 1999) for identifying where a small structural change produces a large shift in a system's behavior. It captures this mechanism's discipline: a cross-system map is only useful if it converges on the few interlocks whose loosening moves the whole outcome. registry ↩