Unmatched count¶
A privacy-preserving survey experiment estimating prevalence of a sensitive trait from differences in mean item counts between randomized lists.
Core Idea¶
The method requires random assignment, no design effects and truthful aggregate counts; ceiling and floor effects, list composition and inattentive responding can bias estimates. A control group reports only how many innocuous statements apply, a treatment group receives the same list plus the sensitive item and the difference in average counts estimates population prevalence without revealing individual answers. The abstraction is therefore identified by a declared carrier, a transformation or constraint over that carrier, and an invariant that tells an analyst whether the named structure is genuinely present.
Scope of Application¶
Unmatched count belongs to survey methodology and is useful where the analyst can specify the typed survey methodology carrier, including objects, relations, parameters, conventions, evidence, boundaries, and comparison targets, then evaluate the target population and sample, sensitive item, control items and list order, random assignment, response count scale, anonymity protocol, group mean estimates and difference, standard error, design-effect tests and assumptions for truthful response are explicit. The scope is broad within that domain but bounded by the need for the target population and sample, sensitive item, control items and list order, random assignment, response count scale, anonymity protocol, group mean estimates and difference, standard error, design-effect tests and assumptions for truthful response are explicit.
Clarity¶
The abstraction clarifies a crowded vocabulary by making the target population and sample, sensitive item, control items and list order, random assignment, response count scale, anonymity protocol, group mean estimates and difference, standard error, design-effect tests and assumptions for truthful response are explicit the center of the account. A claim should name the carrier, the governing operation or relation, the applicable assumptions, and the recognition test.
Manages Complexity¶
Without the abstraction, an analyst must reason directly over many local details: the carrier roles, admissibility assumptions, competing conventions, derived invariants, boundary cases, and proof or validation obligations specific to Unmatched count. Unmatched count compresses them into the roles in the structural signature. That compression permits comparison across instances without erasing the variables that determine validity. It also exposes which details may be varied safely and which are constitutive.
Abstract Reasoning¶
- Identify the carrier. State what the elements, states, objects, or observations are: the typed survey methodology carrier, including objects, relations, parameters, conventions, evidence, boundaries, and comparison targets. Reject examples whose alleged carrier belongs to a different problem. 2. Lock the constitutive rule. Express the target population and sample, sensitive item, control items and list order, random assignment, response count scale, anonymity protocol, group mean estimates and difference, standard error, design-effect tests and assumptions for truthful response are explicit independently of one notation or implementation.
Knowledge Transfer¶
Knowledge transfers strongly among subfields of survey methodology because they reuse the typed survey methodology carrier, including objects, relations, parameters, conventions, evidence, boundaries, and comparison targets, A control group reports only how many innocuous statements apply, a treatment group receives the same list plus the sensitive item and the difference in average counts estimates population prevalence without revealing individual answers., and type the carrier, state every parameter and convention in the definition, test that the target population and sample, sensitive item, control items and list order, random assignment, response count scale, anonymity protocol, group mean estimates and difference, standard error, design-effect tests and assumptions for truthful response are explicit, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases.
Relationships to Other Abstractions¶
Current abstraction Unmatched count Domain-specific
Parents (1) — more general patterns this builds on
-
Unmatched count is a kind of Experimental Design Prime
The proposed strict upward parent is
prime:experimental_design.
Hierarchy paths (2) — routes to 1 parentless root
- Unmatched count → Experimental Design → Control Sample → Comparison → Self Checking
- Unmatched count → Experimental Design → Comparison → Self Checking
Neighborhood in Abstraction Space¶
Unmatched count sits in a crowded region of the domain-specific corpus (27th percentile for distinctiveness): several abstractions share nearly its structure, so a description that fits it tends to fit its neighbors too.
Family — Research Design, Sampling & Metrics (19 abstractions)
Nearest neighbors
- Non-sampling error — 0.95
- Wiki survey — 0.91
- Verification bias — 0.91
- Multiple baseline design — 0.90
- Sampling error — 0.90
Computed from structural-signature embeddings · 2026-09-08