Comparison

slug: comparison

one_liner: Place items in a shared frame along chosen dimensions to read off a relation between them.

review_flags: ACCEPTED as a prime from project-06 (Kurt, 2026-05-29). Promoted from candidate; review_flag history below.

review_flags: CANDIDATE from project-06. CONVERGENT signal: Claude flagged this gap in R9 end-pile (`comparative_method` parking + `experimental_design` parking, both needing a `comparison`/`controlled_comparison` parent); ChatGPT Pro independently surfaced the same gap in its R16 one-shot pass, noting that `contrast` is difference-focused and not broad enough to parent simile/juxtaposition/analogy/benchmarking.

review_flags: Would parent: contrast, juxtaposition, simile, analogy, value_commensuration, comparative_method, experimental_design (controlled comparison is the structural core). Some are CURRENT 2nd-parent candidates.

review_flags: Distinct from `contrast` (which is comparison emphasizing difference), `analogy` (deep structural mapping not just similarity), `commensurability` (need not be common metric).

review_flags: substrate_independence scores are PROPOSER estimates, pending triangulation.

review_flags: 2026-05-28 schema reformat: original project-06 v1 used the 5-section template (Core Idea / Broad Use / Structural Signature / Distinction from Neighbors / Notes); reformatted to the canonical 8-section runbook v1 schema. Structural Signature content folded into Manages Complexity + Abstract Reasoning; project-06 load-bearing rationale preserved in Notes.

core_idea:
Comparison is the structural operation of placing two or more items — the *comparands* — under a shared frame, selecting one or more dimensions along which they will be co-considered, applying an alignment rule that makes them commensurable enough to relate, and reading off an output relation: same or different, greater or lesser, analogous or unmatched, ranked or unranked. The cognitive-science treatment by Holyoak and Thagard (1989) characterizes this as a constraint-satisfaction process running over structural, semantic, and pragmatic constraints — a formal model of the role-slots the operation requires.<!-- FACT-D56-181 -->[^holyoak-thagard-1989] It turns isolated properties of individual items into *relational information* between them. The operation is what cognitive scientists, philosophers of method, and statisticians have all converged on as a foundational move of structured thought — Tversky's (1977) feature-matching account treats similarity itself as the output of a comparison process over weighted feature sets, parameterized by direction and salience.<!-- FACT-D56-182 -->[^tversky-1977]

Comparison can foreground likeness, contrast, ranking, analogy, equivalence, deviation, or fit, but the underlying operation is the same in each case: place the items in commensurable view and read off the relation. Its core commitments are two. First, comparison is **relational** — it generates information *between* items, not *about* a single item considered alone. Second, it is **framed**: comparability requires shared dimensions or criteria, even informal ones. Without a frame, there is no comparison, only juxtaposition; without dimensions, there is no determinate output, only suggestion.

A crucial consequence falls out of the framing condition: comparison names the *operation*, not the *result*. The catalog already contains result-shaped neighbors — `contrast` (the difference reading), `analogy` (the deep-mapping reading), `commensurability` (the precondition that a common metric exists), `classification` (assignment to categories). What none of those name is the underlying move itself: take two or more items, place them in a shared frame, and let a relation appear. Comparison is that move.

structural_signature:
Comparison encodes a structural pattern: **co-framing → dimension selection → alignment → relation read-off**. The pattern separates an unstructured set of items from a structured relational claim about those items, and names the work required to get from one to the other; Gentner's (1983) structure-mapping theory formalizes the same separation in the analogy case, distinguishing the surface-level comparands from the higher-order relational structure that the alignment rule must preserve.<!-- FACT-D56-183 -->[^gentner-1983]

**Recurring features:**

- Two or more items placed under a shared frame
- Dimensions of comparison selected from a larger space
- Alignment rule that makes comparands commensurable
- Output relation (same/different, greater/lesser, analogous, ranked)
- Frame-relativity of the relation produced
- Operation that generates relational information, not properties
- Distinction between the comparing move and its readings

The structural insight is robust across substrates. A perception experiment measuring a just-noticeable difference, a controlled biology trial scoring two genotypes against a phenotype, a literary critic reading a simile, a benchmark suite scoring two language models, a metrologist comparing a sample against a calibration standard — each instantiates the same five-role machinery with different comparands, frames, dimensions, alignment rules, and output relations. Goodman's (1972) sharp critique of bare similarity claims — that similarity is empty without a respect-of-comparison — is the canonical statement of why the dimension-selection role is load-bearing and cannot be elided.<!-- FACT-D56-184 -->[^goodman-1972]

what_it_is_not:
Comparison is **not** a property of a single item. A claim like "this object is large" looks unary but is always implicitly comparative — large *relative to* an implicit reference class. Surfacing the hidden comparand turns covert comparison into explicit comparison, but the operation does not begin when made explicit; it was already running. Comparison is also not the *output* it produces. The output of comparison can be a similarity score, a difference, an ordering, an analogical mapping, or a categorical assignment, but the operation that yields any of these is one and the same.

Nor is comparison reducible to *measurement*. Measurement assigns numerical values to a quantity by comparison against a unit or standard, so every measurement is comparison-shaped — but most comparison is not measurement. A qualitative judgment that two species share a body plan, an analogical mapping between a circuit and a hydraulic system, a literary critic's reading of a simile — these are comparisons that produce relational information without numerical assignment. Comparison is broader than measurement; measurement is comparison specialized to numerical output along a metric dimension, exactly the formal characterization the International Vocabulary of Metrology (JCGM 200:2012) gives by routing every measurement through a calibration chain anchored in a reference standard.<!-- FACT-D56-185 -->[^jcgm-vim-2012]

Comparison is **not** the same as *contrast*, though the two are often used interchangeably in ordinary speech. Contrast is comparison whose dimension selection and output relation are oriented toward *difference*: the operation runs, but the analyst foregrounds the gap rather than the overlap, a foregrounding that Markman and Gentner (1996) show empirically as the *alignable-difference* reading produced by the same structural-alignment machinery that yields commonalities.<!-- FACT-D56-186 -->[^markman-gentner-1996] A contrast is therefore a *kind* of comparison — the difference-emphasizing kind — not a separate operation. The same comparands compared on the same dimensions can yield either a similarity reading or a contrast reading depending on the analyst's interest; the underlying machinery is identical. The DAG edge runs comparison → contrast as presupposes, flipping the historical reverse-subsumption in which contrast (the more familiar English word) was treated as the umbrella — a flip that Markman and Gentner's (1996) demonstration of difference judgments as a *product* of the similarity-comparison process directly supports.<!-- FACT-D56-187 -->[^markman-gentner-1996]

Comparison is not *judgment* or *evaluation*. A comparison can feed into an evaluative judgment (this option is better than that one along criterion X), but the comparison itself produces a relational fact, not a normative ranking. Evaluation requires an additional layer in which one of the read-off relations is privileged as "better" by some external value standard. Plenty of comparisons produce no evaluation at all — comparing two artifacts on age, or two languages on phoneme inventory, generates relational information without imputing value.

Finally, comparison is not *grouping* or *classification*. Classification assigns items to categories; the result of classification is a partition of a set into kinds. Comparison places items in a relation; the result is a structured claim about how they stand to each other. Classification uses comparison as a subroutine (the item is matched against category prototypes or definitions), but adds the act of assignment, which comparison alone does not perform.

broad_use:
**Cognition and perception:** Recognizing similarity, difference, and order is among the most basic cognitive operations. Feature-detection circuits in early visual cortex literally implement comparison operations on adjacent stimuli; psychophysical methods quantify just-noticeable differences as the threshold at which a comparison output flips from "same" to "different." Pre-linguistic infants and non-human animals perform feature-matching and ordinal comparison without methodological scaffolding.

**Scientific method and experimental design:** Controlled comparison — Mill's methods, A/B tests, randomized controlled trials, difference-in-differences designs — is the structural core of causal inference. The experimenter holds the frame constant (matched conditions) and varies one dimension (the treatment), so any output difference is attributable to that dimension rather than to confounders. Campbell and Stanley's (1963) treatment of internal validity is, at its core, an enumeration of the failure modes of the alignment rule in controlled comparisons — selection, history, maturation, and the rest are all ways the frame fails to hold the comparands commensurable.<!-- FACT-D56-188 -->[^campbell-stanley-1963]

**Physics, at the substrate extreme:** CPT-symmetry tests in particle physics — measurements of the proton/antiproton mass ratio, comparisons of meson and antimeson decay rates — are pure controlled comparisons at a substrate where no human practice is in view. The frame is the experimental apparatus, the comparands are matter and antimatter species, the dimension is some observable (mass, lifetime, magnetic moment), the alignment is the symmetry hypothesis being tested, and the output relation is "indistinguishable to within experimental precision." That this is recognizably the same operation as a behavioral A/B test is strong substrate-independence evidence.

**Biology:** Controlled biological comparison — knockout-vs-wildtype crosses, treatment-vs-sham in clinical trials, common-garden experiments holding environment fixed across genotypes — sits between physics and the human-practice domains. Cohort studies and case-control epidemiology extend the same logic to populations where randomization is impossible, with attendant alignment-rule risks (confounding, selection bias) that are the central concerns of the field.

**Literature and rhetoric:** Simile, metaphor, juxtaposition, and parallel structure are comparison used for expressive, persuasive, or evocative effect rather than for inference. Juxtaposition is the pre-comparative setup that supplies comparands and a rough frame without itself performing the dimension selection or alignment — the curator places the two paintings side by side; the viewer runs the comparison. Markman and Gentner (1996) demonstrate experimentally that placing items side by side prompts the viewer to construct an alignment, with commonalities and alignable differences only emerging once the structural-mapping step is actually performed.<!-- FACT-D56-189 -->[^markman-gentner-1996] Hofstadter and Sander's (2013) treatment of analogy as the core of cognition argues that even the most rhetorical-seeming comparisons run on the same dimension-selection and alignment machinery as scientific ones, with the output relation simply weighted toward expressive resonance rather than truth-preservation.<!-- FACT-D56-190 -->[^hofstadter-sander-2013]

**Evaluation and benchmarking:** Comparing options against criteria — cost-benefit analysis, multi-criteria decision analysis, performance benchmark suites — is comparison whose output relation is then fed into a downstream evaluative or selection step. The benchmarking literature in computer science, with its careful attention to held-constant test inputs and varied system-under-test, is comparison's industrial-scale instantiation.

**Analogy and case-based reasoning:** Comparing a current situation to known prior cases to transfer insight is comparison whose alignment rule is structural mapping. Gentner's (1983) structure-mapping theory of analogy specifies the alignment rule precisely — preserve higher-order relational structure, drop surface features — and treats the analogical output as a transferable inferential pattern.<!-- FACT-D56-191 -->[^gentner-1983]

**Measurement and metrology:** Every measurement is a comparison against a unit or reference standard. The international metrology infrastructure — primary standards, calibration chains, traceability — is engineering devoted to making the alignment rule in measurement comparisons trustworthy at scale.

clarity:
A core function of "comparison" as a named prime is to surface the hidden machinery in claims that present as direct readings of the world. An unargued "these are similar," "this is better," or "X is unlike Y" is a comparison output whose comparands, frame, dimensions, and alignment rule have all been left implicit. Naming the operation forces the prior question: similar *under what frame*, along *what dimensions*, by *what alignment rule*? The same two organisms compared on body plan look very different from the same two compared on metabolic pathways; the same two policies compared on cost look very different from the same two compared on equity outcomes. Distinguishing the operation from its readings matters because the readings are not free-standing — they are functions of choices made earlier in the pipeline, and surfacing those choices is the analyst's leverage.

The clarity benefit extends to detecting *covert* comparisons. Claims that look unary — "this is large," "this is fast," "this is unfair" — are comparison outputs in disguise, with the reference class hidden. Naming comparison as a prime makes it natural to ask "compared to what?" and to refuse the claim until the reference is specified.

It also clarifies the structure of disagreement. When two analysts produce different comparison outputs for the same pair of items, the disagreement can be located at any of four sites: they may have chosen different dimensions, applied different alignment rules, used different frames, or simply read the relation differently. Without comparison vocabulary, these disagreements look like flat contradictions; with it, they become locatable and arguable.

manages_complexity:
Comparison decomposes an evaluative situation into five concrete roles: the *comparands* (the items being compared), the *comparison frame* (the shared context in which they are co-considered), the *dimensions* or *criteria* along which the comparison runs, the *alignment rule* that makes the comparands commensurable enough to relate, and the *output relation* — same/different, more/less, analogous, matched, incompatible, or ranked. Medin, Goldstone, and Gentner (1993) argue at length that any usable theory of similarity requires precisely this kind of role-decomposition — most centrally the explicit "respects" along which the comparison runs — without which similarity-talk collapses into the vacuity Goodman warned of.<!-- FACT-D56-192 -->[^medin-goldstone-gentner-1993]

Once those roles are named, an opaque "these are similar" or "this is better" becomes a structured claim with explicit machinery. The analyst can interrogate any single role without challenging the rest: were the comparands appropriately chosen, or was the comparison rigged by cherry-picking? Is the frame neutral, or does it pre-favor one side? Are the dimensions exhaustive, or has the comparison been narrowed to dimensions on which one comparand happens to win? Does the alignment rule force a false commensurability, treating non-equivalent items as equivalent under a metric that does not really apply to both? Auditing the alignment rule is the structural form of methodological critique in experimental design — selection bias, confounding, and equating failures are all alignment-rule failures in disguise — and the same audit transfers to cross-cultural and cross-domain comparison, as Sartori (1991) argues in his account of "cat-dog" miscomparisons: aggregates assembled under an alignment rule that papers over genuine non-equivalence, defeating the comparison from inside.<!-- FACT-D56-193 -->[^sartori-1991] Is the output relation correctly read, or has a same/different distinction been collapsed into a ranking that does not survive scrutiny?

The decomposition converts unargued comparative judgments into auditable ones. This is exactly the move that statistics education makes when it teaches students to distinguish a population, a sample, a treatment, a control, and an outcome measure — all of which are role-slots in a controlled comparison. It is also the move that critical literary analysis makes when it asks "tenor and vehicle?" of a simile. Different vocabularies, same decomposition.

The complexity-management payoff is large. Comparison-shaped problems abound — every claim of similarity, difference, ranking, fit, equivalence, analogy, or categorical match is comparison-shaped — and a single structural vocabulary lets the analyst transfer diagnostic moves across all of them. A trick learned for detecting a rigged frame in a corporate benchmark report is the same trick that detects a rigged frame in a legislative impact analysis.

abstract_reasoning:
Comparison supports the counterfactual move: *if the frame, dimensions, or alignment rule were different, the output relation would change in this specifiable way*. That move is what makes comparison the structural core of controlled experimentation — the experimenter holds the frame constant (matched conditions) and varies one dimension (the treatment), so any output difference is attributable to that dimension. The same abstract operation underwrites benchmarking (hold the task constant, vary the system), analogical reasoning (hold the structural mapping constant, vary the surface domain), and the literary uses (hold the juxtaposition constant, read the relation as expressive content).

A defining feature of comparison is its *frame-relativity*: the same two comparands compare differently along different dimensions, so any comparative claim is implicitly indexed to a frame. Surfacing that index — making the frame explicit — is the abstract reasoning leverage the prime provides. It enables the analyst to construct deliberate counterfactual reframings: "compare these two on cost, then again on equity, then again on durability — and see how the output relation moves." A reframing exercise that would be inarticulate in flat similarity-talk becomes routine in comparison vocabulary.

Comparison also enables a sharp distinction between *robust* and *frame-dependent* relations. A relation that survives reframing across many reasonable dimension choices is robust; one that collapses or inverts under minor reframing is frame-dependent. The robustness question is itself a meta-comparison — comparing the output of comparison under varied frames — and it underpins concepts like external validity in experimental design, generalization in machine learning evaluation, and structural soundness in analogical inference.

knowledge_transfer:
The five-role structure transfers intact across substrates. A biologist comparing two species on phenotype, a metrologist comparing a sample to a calibration standard, a literary critic reading a simile, an economist running a difference-in-differences study, a particle physicist running a CPT test, and a perception researcher measuring a just-noticeable difference are all instantiating the same operation with different comparands, frames, and dimensions; Lijphart's (1971) systematic comparison of the experimental, statistical, and comparative methods in political science is the canonical demonstration that the same role-slots underlie all three traditions, with the differences confined to how each fills the alignment rule.<!-- FACT-D56-194 -->[^lijphart-1971]

The substrate-furthest cases are the strongest transfer evidence. In particle physics, comparison runs entirely without human social or institutional scaffolding — the apparatus implements the frame, nature supplies the comparands, and the output is a number with an uncertainty interval. In early-visual-cortex feature detection, comparison runs in milliseconds in non-human animals and pre-linguistic infants, again without any methodological apparatus. These cases rule out any suspicion that comparison is a specialty of formal science or human reasoning. It is a substrate-independent operation that happens to have particularly powerful institutional implementations in experimental method and benchmarking.

The pedagogical transfer is also clean. A practitioner who has internalized the five-role structure in one domain can use it to diagnose claims in another. An experimental designer can read a literary simile in comparison-vocabulary (what are the comparands, the frame, the implied dimensions of mapping?) and discover that the same machinery is running. A literary critic can read an A/B test in comparison-vocabulary and identify the same role-slots, with different content in each.

formal_abstract:
**Particle physics — CPT symmetry test:** Consider an experiment measuring the magnetic moment of the proton and the antiproton to test the CPT theorem. The comparands are the proton and the antiproton, prepared in a Penning trap. The comparison frame is the apparatus, which by construction holds the magnetic field, trap geometry, and measurement protocol identical for both species. The dimension is the cyclotron-to-Larmor frequency ratio, from which the magnetic moment is extracted. The alignment rule is the assumption that the trap behaves symmetrically with respect to charge sign (a non-trivial assumption requiring its own calibration). The output relation is "the magnetic moments are equal to within experimental precision," and Smorra et al.'s (2017) BASE-collaboration measurement of the antiproton magnetic moment as −2.7928473441(42) nuclear magnetons — agreeing with the proton at the parts-per-billion level — is the current canonical instance.<!-- FACT-D56-195 -->[^smorra-et-al-2017] **Mapped back:** Every role of the comparison operation is filled, and every role can be challenged independently — comparand preparation, frame symmetry, dimension choice, alignment-rule fidelity, output reading. The comparison operation is fully recognizable here, at a substrate maximally far from human practice.

**Controlled biology — common-garden experiment:** Two plant genotypes, A and B, are grown side by side in a common garden under matched soil, water, and light. The comparands are the two genotypes; the frame is the garden, which by design holds environmental factors constant; the dimension is biomass at harvest; the alignment rule is the randomized spatial placement that controls for within-garden microclimate variation; the output relation is "genotype A produces 17% more biomass than genotype B in this environment." The exact same five-role structure governs a Mill's-method causal inference, a difference-in-differences economic study, a benchmark run comparing two language models on a reasoning suite, and a literary simile ("my love is like a red, red rose" — comparands my-love and rose, frame poetic praise, dimensions vitality and freshness, alignment by metaphorical mapping, output relation positive resemblance). **Mapped back:** Comparison is the umbrella; controlled comparison, simile, juxtaposition, and benchmarking are its frame-and-dimension specializations. The same five role-slots run across maximally different content.

applied_industry:
**A/B test on a checkout page:** An e-commerce team compares two checkout-page designs on conversion rate. The comparands are the two page variants; the comparison frame is "users arriving at checkout during the same time window with traffic split randomly"; the dimension is conversion rate; the alignment rule is the randomization, which makes the user populations exchangeable, so any rate difference is attributable to the page rather than to the users; the output relation is "variant B converts at a higher rate." Notice that the same two pages compared on a different dimension — load time, accessibility score, brand consistency — could yield the opposite output relation. The comparison is well-defined only once the frame and dimensions are fixed. **Mapped back:** Industrial A/B testing is a controlled comparison whose alignment rule (randomization) makes the comparison machinery cheap and trustworthy at scale. The same operation that runs in a biology common-garden experiment runs in a checkout-conversion test; the only differences are the comparands, the dimensions, and the alignment-rule implementation.

**LLM benchmark suite:** A team comparing two language models on a reasoning benchmark sets the comparands (the two models), the frame (the benchmark task set, the prompting protocol, the decoding parameters), the dimensions (per-task accuracy, calibration, latency, cost), the alignment rule (identical prompts and grading rubrics applied to both), and the output relation (a per-dimension win/loss/tie record). Benchmark methodology debates — about test-set contamination, prompt sensitivity, grader reliability — are debates about each of these role-slots in turn. **Mapped back:** Modern AI evaluation is comparison at industrial scale, and its methodological pathologies (cherry-picked dimensions, contaminated frames, brittle alignment rules) are diagnosable in exactly the comparison vocabulary the prime supplies.

title: Frame neutrality is rarely achievable, but frame partiality is rarely detectable

body: Comparison requires a shared frame; the frame is usually chosen by the analyst; an analyst with a stake in the output has every incentive to choose a frame that favors a preferred comparand. Detecting frame partiality from the outside requires constructing alternative frames and seeing whether the output relation moves — but alternative frames are themselves chosen by the critic, who may have opposing stakes. Frame neutrality is more an aspiration than an achievable state. The tension is unavoidable: every comparison is frame-relative, every frame is chosen, and every chooser has interests. The practical response is *triangulation* — reporting comparison outputs under multiple frames and being transparent about the choice space — but triangulation is costly and is itself comparison.

title: Dimension selection trades exhaustiveness against tractability

body: A comparison along one dimension is tractable but narrow; comparison along many dimensions is exhaustive but produces a multi-dimensional output that may not collapse into a single relation. Multi-criteria decision analysis can produce Pareto-dominance verdicts ("A beats B on every dimension") but more often produces Pareto-incomparability ("A wins on cost, B wins on durability"), which is a comparison-output that does not yield a clean ranking. The tension between rich and decidable comparison is structural: adding dimensions increases fidelity but reduces the chance of a clean output, and the analyst must choose where on this curve to sit.

title: Alignment rules can force false commensurability

body: Making comparands commensurable requires an alignment rule; aggressive alignment can paper over genuine non-equivalence. Comparing student test scores across school districts requires alignment rules (curriculum equivalence, test-form equating, demographic weighting) any of which can force commensurability where it does not really hold. The tension is that without an alignment rule there is no comparison, but with too strong an alignment rule the comparison conceals the differences it purports to measure. The "apples and oranges" complaint is precisely a complaint about alignment-rule overreach.

title: Comparison can be morally weaponized by selective framing

body: Every comparison output is consumable as evaluation, and the framing of any comparison can be steered toward an evaluative conclusion. Comparing two policies on cost but not on equity, two groups on income but not on opportunity, two artists on technique but not on intent — each is a comparison whose framing pre-determines the evaluative reception. Comparison is morally neutral as an operation but morally loaded in deployment; the same prime that underwrites careful science underwrites tendentious rhetoric. Naming comparison as a prime helps surface this, but the same machinery is at work.

title: Operation-versus-result conflation is structurally persistent

body: The same word "comparison" denotes both the operation and its output, and the ambiguity infects ordinary speech and even technical practice. "Run a comparison" denotes the operation; "the comparison shows X" denotes the output; "the comparison is unfair" can be either — unfair operation, or unfair output read off a fair operation. The tension is that the language does not distinguish the levels, so the analyst must keep them distinct in thought even when the vocabulary blurs them. Treating comparison as a prime — explicitly the operation, with separate names for each kind of output — is the principled response, but it does not eliminate the slippage.

title: Comparison produces relational information, but stakeholders demand absolute claims

body: A comparison output is intrinsically relational — A is greater than B, A is similar to B — but downstream consumers often need an absolute claim ("A is good") or a context-free ranking ("A is best"). Converting relational outputs into absolute claims requires a further step (an external standard, an aggregation, a normative interpretation) not part of the comparison operation. Comparison is the cleanest tool for generating defensible relational claims and a poor tool for absolute ones, yet consumers persistently treat its outputs as absolute. Reviewers of benchmarks, ratings, and impact assessments routinely make this slippage.

prose:
1. **Five-role decomposition:** When faced with an opaque or contested comparative claim, decompose it into comparands, frame, dimensions, alignment rule, and output relation. Interrogate each role separately. This is the workhorse archetype: it converts unargued comparisons into auditable ones and is the prerequisite for every other intervention.

2. **Frame triangulation:** When a comparison output is suspected to be frame-dependent, run the same comparison under multiple alternative frames and report the output under each. Robust relations survive triangulation; frame-dependent ones do not. This archetype is the practical answer to T1 (frame neutrality is unachievable but frame partiality is rarely detectable) and is the implicit logic behind sensitivity analysis in empirical work.

3. **Dimension expansion:** When a comparison is suspected of being narrowed to dimensions favoring one comparand, expand the dimension set and re-run. Pareto-dominance verdicts ("A beats B on every dimension") are strong; Pareto-incomparability ("A wins on cost, B wins on durability") is also informative, because it locates the disagreement at a specific dimension trade-off rather than concealing it in a single-dimension verdict.

4. **Alignment-rule audit:** When apples-and-oranges concerns arise, examine the alignment rule explicitly. Does it force commensurability where genuine non-equivalence exists? Are there comparands the rule cannot legitimately bring into common view? Alignment-rule audits are the structural form of methodological critique in experimental design (selection bias, confounding, equating failures) and in cross-cultural or cross-domain comparison generally.

5. **Operation/output disambiguation:** When a comparison is criticized as "unfair," ask whether the operation is malformed (rigged frame, biased dimensions, broken alignment) or whether the output is being read inappropriately (relational output being treated as absolute, single-dimension output being treated as overall). Disambiguating the level of the complaint is the prerequisite for fixing it.

6. **Controlled-comparison upgrade:** When an informal comparison is producing disputed outputs, upgrade to controlled comparison: hold the frame constant (matched conditions), vary one dimension (the treatment), randomize to control unobserved variation. The upgrade is costly but converts a comparison whose alignment rule is suspect into one whose alignment rule is enforced by experimental design.

notes:
This is the long-orphaned umbrella the project flagged in R9 when `comparative_method` and `experimental_design` had no clean parent, because `comparison` and `controlled_comparison` were both absent from the catalog. ChatGPT Pro's R16 pass independently surfaced the same gap with the same slug, an unusual convergent signal that lent weight to the case for promoting comparison from candidate to accepted prime. Once `comparison` is in place, `contrast` becomes a presupposes child (R17a retype, formerly subsumption — contrast is comparison oriented toward difference, not a sibling). `simile → comparison` and `analogy → comparison` are decompose edges (each specifies the alignment rule and output-relation type). The `experimental_design → comparison` decompose edge captures R9's structural-core observation: controlled comparison is the inferential heart of experimental design. `value_commensuration → comparison` is presupposes, because value commensuration requires that a comparison along a value dimension be performable.

Comparison's substrate-furthest cases — CPT-symmetry tests in particle physics, controlled experimental comparison in biology — are deliberately spotlighted in the Broad Use and Examples sections because they answer the most common skeptical move against comparison as a prime ("isn't this just a human-cognitive thing?"). The particle-physics case in particular runs the comparison machinery entirely without human social or institutional scaffolding, which is the cleanest available evidence for substrate independence.

The frame-relativity feature is the single most under-appreciated aspect of the prime. In ordinary speech, comparison outputs are routinely treated as frame-free properties of the comparands ("these two are similar," "this one is better"), when they are in fact joint outputs of the comparands, the frame, the dimensions, and the alignment rule. Naming the frame as a load-bearing role-slot — and treating "compared to what, along what dimensions, under what alignment?" as a routine prompt — is the practical reasoning leverage the prime supplies.

A frequent confusion to watch for in curation is the operation/result conflation. New candidate primes presented as "kinds of relation" (sameness, difference, ranking, fit, equivalence) are almost always comparison outputs rather than separate operations; the right test is whether the candidate can be reached by specifying the frame, dimension set, alignment rule, and output-relation reading on the comparison operation — if so, it is a child, not a sibling.


Compatibility

type: prime

slug: compatibility

one_liner: The relational condition under which two or more entities can coexist or compose without breakage, interference, or contradiction.

status: draft

core_idea:
Compatibility is the capacity of two or more entities—systems, components, standards, formats, agents, processes—to coexist, interact, or compose without breakage, interference, or contradiction. It names a relational property: not an intrinsic quality of a single entity, but a condition between entities, an attribute Rogers (2003) places at the center of his classic account of how innovations diffuse through social systems. <!-- FACT-D52-106 -->[^rogers-2003] A plug and socket are compatible when their physical and electrical signatures align; a library version and an application are compatible when their API contracts align; a blood type and a recipient's immune system are compatible when immune rejection does not occur; an organizational culture and a new hire are compatible when social norms and values align sufficiently.

Compatibility is **passive coexistence without conflict**, distinct from active interoperability (which requires coordinated function) and integration (which requires tight coupling). Two systems can be compatible without ever interacting: gasoline and air are compatible (they coexist in a fuel tank) even when unmixed. A software library can be backward-compatible (old code runs unchanged) without being forward-compatible (new code may break on older versions), a distinction Tanenbaum and Van Steen (2017) develop in their canonical treatment of openness in distributed systems. <!-- FACT-D52-107 -->[^tanenbaum-vansteen-2017]

structural_signature:
Compatibility encodes a signature pattern: **interface-alignment × constraint-satisfaction → safe-composition**. It separates entities that can occupy the same space or regime from those that cannot. The pattern holds across domains.

**Recurring features:**

- Relational property between two or more entities
- Interface alignment and boundary conditions
- Constraint satisfaction without renegotiation
- Passive coexistence versus active interaction
- Tolerance matching and regime overlap
- Absence of mutual exclusion or contradiction
- Composition without friction or hidden costs

The structural logic is robust: whether checking a mechanical fit (tolerance stack-up), a software library version (API contract), an immunological match (antigen-antibody binding), or a cultural fit (organizational values), the reasoning is identical. Two entities are compatible if their operating regimes, interfaces, or constraint sets overlap without contradiction, a substrate-agnostic pattern Bass, Clements, and Kazman (2012) treat as one of the central quality attributes in software architecture practice and which generalizes naturally to non-software domains. <!-- FACT-D52-108 -->[^bass-clements-kazman-2012]

what_it_is_not:
Compatibility is **not** identity or sameness. Two systems can be compatible while remaining entirely different. A laptop charger and outlet are compatible not because they are identical but because their voltage, frequency, and connector specifications align. A SQL database and a Python ORM are compatible not because they use the same language but because the ORM implements the SQL protocol correctly. Confusing compatibility with sameness leads to costly over-specification: requiring all systems to be identical or closely similar when compatibility through interface specification would suffice.

It is **not** universal functionality or perfect fit. Compatibility specifies only that systems do not break each other, not that they perform optimally together. A vintage mechanical watch and a modern wrist-mounted computer are compatible in the sense that they can both occupy your wrist, but their functional interaction is minimal; they are compatible in coexistence, not in capability. Optimal pairing (both systems enhancing each other) is a higher requirement than mere compatibility (coexistence without conflict).

Compatibility is **not** interchangeability or substitutability. Two keyboard layouts (QWERTY and Dvorak) are mutually incompatible for a user in a single session, but a keyboard supporting both layouts is compatible with both. This is compatibility via **adaptation**, not inherent interchangeability—the structural pattern Gamma, Helm, Johnson, and Vlissides (1994) formalize in the Adapter and Bridge design patterns. <!-- FACT-D52-109 -->[^gamma-et-al-1994] The ability to coexist through adaptation is far more powerful than requiring all systems to be directly interchangeable.

Nor is it a property independent of context. Compatibility is always relative to a specific regime (operating temperature, voltage range, API version, organizational context). A component rated for −20°C to 80°C may be compatible with a high-altitude aircraft (−50°C) or a desert vehicle (60°C) only under specified conditions. Compatibility claims without regime specification are incomplete and misleading. A statement like "fully compatible" is meaningless without specifying which operating conditions, versions, or contexts the claim covers.

broad_use:
**Engineering & materials:** Mechanical tolerances and fits (clearance, interference, line fits), electrical compatibility (voltage, frequency, impedance), material compatibility (corrosion, diffusion, alloy formation), connector standards (USB, HDMI, electrical plugs), thermal compatibility (expansion coefficients, operating ranges).

**Software engineering:** Binary compatibility (ABI stability), source compatibility (API contracts), version compatibility (semantic versioning, formalized by Preston-Werner (2013) as a contract for backward-compatibility communication), format compatibility (file formats, compression codecs), protocol compatibility (HTTP versions, messaging standards), hardware compatibility (processor instruction sets, memory requirements). <!-- FACT-D52-110 -->[^preston-werner-2013]

**Biology & medicine:** Immunological compatibility (blood type matching, organ transplant compatibility), genetic compatibility (in breeding, disease resistance), vaccine compatibility (immune response, drug interactions), microbiome compatibility (commensal and pathogenic relationships).

**Ecology & invasive species:** Species compatibility in ecosystem introductions, predator–prey relationship balance, resource competition, niche overlap, invasive-species impact on native fauna and flora.

**Social systems:** Interpersonal compatibility in teams and partnerships (personality, communication style, values), organizational culture compatibility (mission alignment, norm fit, treated as a foundational concept by Schein (1985)), cultural compatibility in multicultural settings, cross-organizational collaboration (process alignment, incentive structures). <!-- FACT-D52-111 -->[^schein-1985]

**Operations & logistics:** Component interchangeability in supply chains, equipment compatibility in integrated systems, standard compliance (ISO, ANSI, regulatory certification), scheduling compatibility in multi-party coordination.

**Law & regulation:** Regulatory harmonization across jurisdictions, legal compatibility (contract enforceability, property rights), data protection compatibility (GDPR compliance, privacy laws), standards compatibility (emissions standards, safety codes).

clarity:
A primary function of "compatibility" is to clarify the **boundary condition between composition and conflict**. It surfaces whether systems can be safely combined and at what cost. A software team releasing a library must answer: Is this version compatible with existing applications? If yes, users can upgrade without code changes; if no, a compatibility layer (adapter, bridge, shim) is required, or users must remain on the old version indefinitely. This question has serious consequences for users, vendors, and entire ecosystems.

Compatibility also distinguishes between **tight coupling** (systems are mutually dependent, a change in one breaks the other) and **loose coupling** (systems are independent, compatibility is optional). A Unix shell command and a Python script are loosely coupled: they interact via standard pipes; if either is improved, the other continues working—the canonical illustration of the Unix philosophy described by Kernighan and Pike (1984), in which power emerges from relationships among small, composable programs sharing a uniform text-stream interface. <!-- FACT-D52-117 -->[^kernighan-pike-1984] A Java subclass and its parent class are tightly coupled: a change to the parent can break the child. Understanding where systems fall on this spectrum is crucial for system design and evolution strategy.

Furthermore, clarity comes from naming **which regime** compatibility applies to. A software library may be compatible with Python 3.8–3.12 but not 3.6. A drug may be compatible with certain foods (no interaction) but incompatible with others (fatal interaction). Specifying the regime prevents false claims of universal compatibility. Without explicit regime specification, compatibility claims are vacuous: "Is it compatible?" becomes unanswerable without asking "Compatible in what context, version, configuration, or environment?"

manages_complexity:
Compatibility reduces the combinatorial explosion of potential interactions. Without it, testing every possible combination of components would be infeasible: if you have 10 libraries each with 5 versions, that is 5^10 combinations to test. Compatibility simplifies this by establishing contracts: if you meet the interface and constraints, you are compatible; if you do not, you are not. Designers can reason about composition without exhaustive testing—the principle Parnas (1972) established as the foundation of modular system design through information hiding. <!-- FACT-D52-112 -->[^parnas-1972]

It also enables **incremental system design**. An architect can specify a component's required interface without knowing the internal implementation of components that will connect to it. Backward compatibility means that applications written for version 1.0 of a library will run on version 1.5 without modification; forward compatibility means version 1.5 applications will run on version 1.0 if they use only pre-existing APIs. This lets teams evolve systems in parallel without constant renegotiation.

In operations, compatibility simplifies supply chains. If a replacement part is compatible with existing equipment, it can be swapped without redesign, retesting, or retraining. This is how modular systems scale.

abstract_reasoning:
Compatibility encourages thinking about systems in terms of **interfaces, constraints, and contracts** rather than implementation details. A software developer need not know how a database engine works internally; they need only understand the SQL interface and the guarantees the database makes (ACID properties, indexed column performance). This abstraction enables reasoning about large systems without cognitive overload.

It also enables **counterfactual reasoning** about evolution and failure. What would happen if we released a breaking API change? The answer is immediate: some applications become incompatible, requiring refactoring. What if we moved from a proprietary data format to an open standard? Compatibility would increase; applications from multiple vendors could interoperate. This reasoning clarifies trade-offs before decisions are made—an analytical move Lehman (1980) made central to his laws of software evolution, where continuing change requires explicit reasoning about what compatibility guarantees survive each release. <!-- FACT-D52-113 -->[^lehman-1980]

Furthermore, compatibility reasoning highlights **single points of failure**. If a system's compatibility depends on a proprietary standard held by one vendor, evolution of that standard can break everything downstream. Recognizing this guides choices toward open standards, modularity, and redundancy.

knowledge_transfer:
The compatibility pattern transfers powerfully across domains. The reasoning behind software API contracts (specify what clients can rely on) is identical to the reasoning behind medical drug interactions (specify which combinations are safe). The thinking behind component tolerance stacking (accumulate uncertainties in fits) parallels the thinking behind organizational culture fit (accumulate norms and values). A chemical engineer reasoning about alloy compatibility (which metals form brittle phases when mixed) can recognize the parallel to team dynamics (which personality types create friction)—a transfer Garlan, Allen, and Ockerbloom (1995) anchor in their seminal analysis of architectural mismatch, where the same constraint-violation logic explains why building systems out of existing parts is hard across very different substrates. <!-- FACT-D52-114 -->[^garlan-allen-ockerbloom-1995]

Tools from one domain transfer: **compatibility matrices** (used in software versioning to show which versions work with which platforms) apply to supply-chain management, team composition, and regulatory compliance. **Backward-compatibility testing** in software (regression testing, version-pair testing) parallels quality-assurance logic in equipment maintenance and drug approval, as Beizer (1990) systematizes in his foundational treatment of software testing techniques. <!-- FACT-D52-118 -->[^beizer-1990] Understanding one illuminates the other.

formal_abstract:
**Software library versioning:** A Python library `requests` releases version 2.31.0 with a new `timeout` parameter in a commonly used function. Old code passing positional arguments continues to work (backward compatible). New code using the new parameter works only on version 2.31.0+. A downstream application depending on `requests >= 2.20.0` is compatible with both old and new versions; an application depending on `requests >= 2.31.0` is incompatible with version 2.20.0. Compatibility is not binary (compatible or not) but **version-specific**: you must specify the range. When a library releases version 3.0.0 with a completely restructured API, all applications using version 2.x become incompatible; they will not run without code modification. **Mapped back:** Compatibility is conditional on interface alignment. The same concept applies to biological compatibility: a donor organ is compatible with a recipient only if blood type, tissue antigens, and size constraints align; a mismatch in any dimension breaks compatibility.

**Material compatibility in manufacturing:** An engineer designing an aerospace component must select materials that remain compatible across operating conditions: thermal expansion coefficients that do not exceed a tolerance (otherwise internal stress develops), corrosion resistance to avoid galvanic attack at interfaces, and fatigue resistance to prevent crack initiation. A titanium-aluminum joint in an aircraft wing must satisfy all three constraints simultaneously. If one constraint is violated, the materials are incompatible and the part fails in service. The engineer consults compatibility charts (tables of material pairs and their suitability across temperature and load regimes) much as a software engineer consults version-compatibility tables. **Mapped back:** Both represent the same structure: entities (materials, library versions) are compatible only when their constraints align in the operating regime (temperature and stress; API version and client code).

applied_industry:
**Medical drug compatibility:** A patient on anticoagulant therapy (blood thinner) must avoid NSAIDs like ibuprofen because they are incompatible—ibuprofen increases bleeding risk, a critical interaction. The patient's medical record must flag this incompatibility. A clinician cannot simply prescribe any pain reliever; they must check compatibility. Some drugs have broad compatibility (acetaminophen is compatible with most other drugs); others have narrow compatibility (certain anticonvulsants interact with hormonal birth control). Compatibility is not a property of the drug alone but of the pair (or triple, or n-tuple) of drugs in a specific patient. **Mapped back:** Like software, medical compatibility requires regime specification (patient age, liver function, other medications) and can be represented as a matrix (drug × drug → compatible/incompatible).

**Organizational culture and acquisition:** Company A acquires Company B. Their cultures are incompatible if A's emphasis on hierarchy and B's emphasis on flat structures create conflict; if A prioritizes short-term profit and B prioritizes long-term sustainability, incompatibility develops. Successful acquisition requires either achieving **cultural compatibility** (through assimilation or deliberate hybrid culture) or **structural compatibility** (keeping teams separate so different cultures do not interact). Some organizations merge cultures; others maintain subsidiaries as autonomous units—a compatibility strategy via separation, a trade-off Cartwright and Cooper (1993) document empirically in their study of cultural compatibility as a determinant of merger success. This parallels how software systems achieve compatibility via adapters and bridges when native compatibility is impossible. <!-- FACT-D52-115 -->[^cartwright-cooper-1993]

**Ecosystem introduction:** Introducing a non-native plant species into an ecosystem raises compatibility questions. Is the species compatible with native pollinators? With native predators? With soil microbiota? With water availability? Invasive species often succeed because they are **incompatible with native predators** (no natural enemy to control population) while being **compatible with native resources** (they exploit a niche no native plant occupies efficiently). Understanding compatibility profiles allows ecologists to predict invasive success and design mitigation. **Mapped back:** Ecosystem compatibility is like software plug-compatibility: success depends on how well interfaces align with existing systems.

title: Backward compatibility versus forward compatibility creates path dependence

body: Backward compatibility (new versions support old code) is valued because it protects legacy systems and enables smooth transitions. But it locks in old interfaces, preventing evolution. Forward compatibility (old versions support new code) is impossible without predicting the future. Standards bodies must choose: guarantee backward compatibility (slower evolution, technical debt accumulation) or allow breaking changes (faster innovation, user disruption). The costs of each path are real and deferred to different stakeholders. Early adopters bear cost when breaking changes occur; late adopters bear cost when technical debt from backward compatibility constrains new capability.

title: Universal compatibility versus optimized compatibility creates efficiency trade-offs

body: Designing for universal compatibility (supporting every platform, every configuration, every legacy system) is conservative but expensive. Every feature costs more to implement across broader compatibility. Designing for narrow compatibility (optimized for specific use cases) is efficient but excludes users. A software library can support Python 2 and 3, which doubles test burden and maintenance cost, or drop Python 2 and move fast. A medical device can support a broad range of anatomies and physiologies, or a narrow range at lower cost. The tension is real: universal compatibility is not free.

title: Compatibility by design versus compatibility by adapter creates system-complexity boundaries

body: Some systems are designed for compatibility from the start (Unix pipes, standard electrical outlets, modular furniture); others are retrofitted with compatibility layers (software emulation, protocol translators, mechanical adapters). Compatibility by design is elegant but constrains the original system (slower innovation, lowest-common-denominator features). Compatibility by adapter is flexible but adds complexity and performance overhead (translation costs, edge cases, hidden failures). An organization can redesign its systems for compatibility or build bridges; each approach has merit and cost.

title: Compatibility lock-in versus flexibility creates long-term risk

body: Strong compatibility guarantees (we will support this interface forever) provide certainty for users building on the platform but limit the platform's evolution. A company committed to supporting an old API cannot easily migrate users to a better architecture. Weak guarantees (compatibility not assured) provide flexibility but create uncertainty. Users cannot confidently invest in building on the platform. The tension is between **user certainty** (they can plan long-term) and **platform flexibility** (we can evolve). Markets often resolve this by allowing both: some vendors promise stability (compatibility), others promise innovation (regular breaking changes) and attract different user bases.

title: Partial compatibility as a hidden failure mode

body: Two systems can be partially compatible: they work in 90% of scenarios but fail catastrophically in the remaining 10%. This is more dangerous than clear incompatibility, which forces explicit design for adaptation. A database driver that works with most queries but crashes on complex joins is partially compatible and insidious. A medication that is compatible with most other drugs but causes fatal interaction with a few is partially compatible and deadly, a class of risks Hansten and Horn (2003) document in their canonical reference on clinical drug-interaction management. Partial compatibility can escape notice in testing and cause failures in production or clinical use. The danger is that users may assume compatibility is binary (yes or no) and fail to test edge cases. <!-- FACT-D52-116 -->[^hansten-horn-2003]

title: Compatibility as stabilizer versus compatibility as obstacle creates system-design paradoxes

body: In some systems, compatibility is protective: a high-friction interface that prevents accidental breaking changes, a regulatory requirement that prevents race-to-the-bottom, a formal specification that prevents misunderstanding. Reflexively lowering compatibility barriers for speed or convenience can destabilize systems that depend on that friction. A voting system's requirement for supermajority consensus creates friction (low compatibility with simple majoritarian change) that protects minority rights. A software library's strict backward-compatibility requirement creates friction (vendors cannot remove deprecated functions) that protects legacy code. Yet the same friction, in a different context, is a barrier to progress. The question "Should we increase compatibility?" requires asking "What stability does the current incompatibility provide?"

prose:
1. **Specification and certification:** Establish explicit interface contracts, constraint definitions, and regime boundaries. Software: API versioning, semantic versioning, integration tests. Materials: tolerance charts, alloy phase diagrams, compatibility matrices. Biology: blood-type classification, allergen panels. This makes compatibility verifiable and communicable.

2. **Adapter and bridge patterns:** When native compatibility is expensive or impossible, introduce a translation layer. Software: protocol adapters (HTTP to gRPC), ORM (object-relational mapping), emulation layers. Materials: mechanical adapters, epoxy bonds between incompatible materials. Organizations: liaison roles, cultural translators. Adapters add cost but preserve ecosystem diversity.

3. **Modular design with clear boundaries:** Separate systems into modules with well-defined interfaces so that changing internals does not affect compatibility. Plugins, microservices, componentized products, and loose-coupling patterns enable teams to evolve modules independently while maintaining compatibility across module boundaries.

4. **Backward-compatibility testing and regression suites:** Build continuous testing that verifies old code continues working with new versions. Catch breaking changes before they reach users. This is standard in mature software (regression test suites run on every build) and less common in other domains but applies similarly to medical devices, equipment, and regulatory compliance.

5. **Graceful degradation and feature negotiation:** Instead of binary compatibility, systems can negotiate capability levels. HTTP/2 and HTTP/1.1 clients negotiate which protocol to use; modern and legacy equipment can negotiate which features to use. This enables broader compatibility without sacrificing capability for advanced users.

6. **Regime specification and constraint documentation:** Make explicit which conditions, versions, configurations, and use cases are supported. "Compatible with Python 3.8–3.11" is clearer than "compatible with modern Python." "Compatible with temperature −20°C to 80°C" is clearer than "compatible with normal conditions." Users and integrators can then make informed decisions about risk and necessity.

### Catalog cross-references (v1, batches 02–29)

Solution archetypes that reference this prime (per `solution_archetypes/_catalog/catalog_v1_batches_02_29.yaml`):

**As related prime (1):** `slot_template_design`

notes:
Compatibility is often conflated with interoperability, but they differ: compatibility is passive coexistence without conflict; interoperability requires active, coordinated interaction—the very distinction Postel (1980) crystallized as the robustness principle in RFC 760, instructing implementations to be conservative in what they send and liberal in what they accept so that compatibility precedes and enables interoperation. <!-- FACT-D52-119 -->[^postel-1980] Two electrical outlets in different countries may be incompatible (you need an adapter), but if you adapt them, they become interoperable (you can plug in and use the device).

The concept of **emerging incompatibilities at scale** is critical. Two systems might be individually compatible with a standard and yet incompatible with each other due to subtle differences in how they implement the standard. This is common in software (two libraries both implement JSON correctly but make different assumptions about field ordering or whitespace) and in biology (a medication compatible with each of a patient's other medications individually can cause harmful interactions in combination).

Compatibility also carries **temporal dynamics**: systems can be compatible at one time and incompatible at another. A chemical reaction that is kinetically frozen (takes millennia to occur) at room temperature becomes fast (and thus a concern for safety) at elevated temperature. A social norm that is stable (most people follow it) at one moment becomes unstable (people abandon it) when critical mass shifts. Time and context change compatibility.

Finally, compatibility reasoning often assumes that incompatibility is fixable via design; sometimes it is not. A molecule cannot be both hydrophobic and hydrophilic simultaneously in the same region (they are thermodynamically incompatible), as Hildebrand and Scott (1950) formalize through solubility parameters that quantify the cohesive-energy mismatch driving phase separation. A person cannot simultaneously have contradictory values (loyalty and honesty can clash). <!-- FACT-D52-120 -->[^hildebrand-scott-1950] Recognizing hard incompatibility—as distinct from fixable design flaws—prevents wasted effort and clarifies true trade-offs.


Compellence

slug: compellence

one_liner: Imposing ongoing costs to force a positive action and keeping them live until compliance — the action-demanding counterpart to deterrence, structurally harder because compliance is publicly visible and deadline-bound.

core_idea:
Compellence is the structural pattern of imposing ongoing costs on a target to *force a
positive action* — and crucially, to keep imposing those costs until the action is
performed. It is the active, action-demanding counterpart to deterrence, which imposes
costs *if* a proscribed action is taken and so succeeds invisibly, in the form of
non-events. Compellence's signature commitments are a *positive demand* (do X) rather than
a prohibition; a *continuing pressure* that remains live until compliance, not a one-shot
threat; a *release condition* that the target can identify and act on; and a *face-saving
exit* that lets compliance be visible without being publicly humiliating.

The foundational observation is that compellence is structurally *harder* than deterrence
even though they look symmetric on the surface, and the reasons are substrate-independent.
Compliance with compellence is publicly observable — the target moves first, visibly, on
the compeller's terms — whereas successful deterrence is invisible, since the target simply
does not act. Compellence has an unambiguous timeline (when must X happen?) that deterrence
lacks. And compellence requires a reputational concession from the target in a way
deterrence does not. These three asymmetries are why a symmetrically scaled compellent
posture under-performs an equivalent deterrent one, and why the bottleneck is so often the
target's *visible compliance* rather than the magnitude of pressure.

This prime sits at the framed end of the spectrum, and the grading records it as among the
most framed in the batch. Its vocabulary and analysis are bound to coercion theory, it
carries heavy normative load (coercive use is the paradigm case), it presupposes a
human-practice context of strategic actors, and importing it into other domains brings the
international-relations interpretive frame with it. The structure is real and travels, but
it travels *as a framed concept* — a named strategic instrument — rather than as a
substrate-neutral mechanism.

structural_signature:
*the positive action-demand* — *the continuing (not trigger-reserved) pressure* — *the target-recognisable release condition* — *the face-saving exit* — *the visible-compliance bottleneck* — *the asymmetry-with-prohibition invariant*

A coercive arrangement exhibits the compellence pattern when each of the following holds:

- **A positive demand.** The coercer requires the target to *perform* an action (do X), not merely to refrain from one. The demanded act, not its absence, is the success condition.
- **Continuing pressure.** Costs are imposed and held live until compliance, rather than reserved against a future trigger. Lifting or pausing the pressure prematurely undoes the campaign — the inverse of the trigger-reserved posture of prohibition-coercion.
- **A release condition.** There is a threshold the target can identify and act on, such that performing the demanded action visibly terminates the pressure. Without a recognisable release, the target cannot rationally comply.
- **A face-saving exit.** A design feature lets compliance occur without public humiliation, so the target can choose the demanded action despite its reputational cost.
- **The visible-compliance bottleneck.** Compliance is publicly observable: the target must move first, on the coercer's terms, by a deadline. The binding constraint is typically this visibility, not the raw magnitude of pressure.
- **The prohibition asymmetry invariant.** Because compliance is observable, deadline-bound, and reputationally costly, action-forcing coercion is structurally harder than the symmetric prohibition-enforcing case (whose success is an invisible non-event), so equal scaling under-performs.

The components compose a directional instrument: a positive demand backed by continuing pressure, terminable at a target-recognisable release, made choosable by a face-saving exit — with visible compliance, not pressure magnitude, as the usual point of failure.

what_it_is_not:
- **Not deterrence.** `deterrence` imposes a cost *if* a proscribed action is taken, succeeding invisibly as a non-event; compellence imposes continuing cost *until* a positive action is performed, succeeding visibly and on a deadline. They are siblings under a coercion parent, structurally inverted in demand, timeline, and observability of success.
- **Not a one-shot precommitment.** `commitment_device` binds one's own future choices; compellence applies continuing external pressure on *another* agent until they act. A commitment device may *make* a compellent threat credible, but it is not the coercion itself.
- **Not sunk-cost lock-in.** `sunk_cost_and_irreversible_commitment` describes a *self-imposed* continuation pressure from what has already been spent; compellence is the deliberate continuing pressure aimed *outward* at a target. The two feel identical from inside the compeller (both say "keep pushing"), which is exactly the trap, but one is strategy and the other is bias.
- **Not held-back capacity.** `reserve` is unused capacity hedged against uncertainty; compellence is the *active application* of pressure, not its withholding.
- **Not preserved future choice.** `optionality` keeps options open; compellence forecloses the target's option to refuse by making refusal continuously costly — a demand for a specific action, not a preservation of flexibility.
- **Common misclassification.** Reading any structured incentive or contract deadline as compellence. The frame is load-bearing only when a target is being *coerced* into a positive action against its interest, with continuing pressure and a deadline; an ordinary price signal or voluntary deadline imports an adversarial zero-sum interpretation that distorts the analysis toward escalation logic.

broad_use:
- **International relations** (origin): coercive bombing demanding withdrawal, blockades
  demanding policy change, sanctions regimes demanding behaviour change — the 1962 Cuban
  quarantine was compellence (force missile withdrawal), not deterrence.<!-- FACT-D59-901 -->[^schelling-1966]
- **Labor relations**: a strike is compellence (continuing economic pressure until wage
  concessions), a threatened strike before expiry is deterrence, and a lockout is the
  symmetrical employer-side move.<!-- FACT-D59-902 -->[^schelling-1960]
- **Regulatory enforcement**: continuing daily fines until a violation is corrected
  (per-diem penalties) are compellence, while one-shot fines for completed violations are
  deterrence.<!-- FACT-D59-903 -->[^acus-civil-penalties]
- **Debt collection and ransomware**: escalating collection actions that remain in force
  until payment, and encryption-until-paid, are compellence engines — costs continue until
  the demanded act is performed.
- **Hostage negotiation and parenting**: a captor's continuing threat is compellence, and
  the negotiation partly supplies a face-saving exit; "no TV until your homework is done"
  is compellence, while "if you hit your sister you lose TV" is deterrence.<!-- FACT-D59-904 -->[^schelling-1966]
- **Software, platforms, and economic sanctions**: forced upgrades with continuing
  degradation until update, bot-detection challenges blocking service until verified, and
  secondary-sanctions regimes escalating until a state changes policy.<!-- FACT-D59-905 -->[^atlantic-council-secondary-sanctions]

clarity:
Naming compellence clarifies that a coercive demand is doing one of two structurally
different jobs, with different success criteria and different failure modes. The analyst who
confuses them measures the wrong thing: deterrence success is non-events, impossible to
count directly, while compellence success is visible target action by a deadline. The
analyst also misdiagnoses failures — deterrence often fails silently (the target acts
anyway) and is then mistaken for "the threat wasn't credible," while compellence often fails
visibly (the target refuses or stalls) and is then mistaken for "we need more pressure" when
the actual problem is the absence of a face-saving exit.

The naming also clarifies the *asymmetric difficulty*. A practitioner designing a compellent
campaign learns to expect it to be harder, take longer, cost more, and require more
attention to the target's exit conditions than a symmetrically scaled deterrent posture
would. This converts a common strategic error — scaling pressure as if compellence and
deterrence were interchangeable — into an explicit design caution. The clarifying force is to
force the analyst to ask, of any coercive instrument, whether it is being used to *force an
action* (compellence, success visible and deadline-bound) or to *prevent one* (deterrence,
success invisible), because the two demand different success criteria, different timelines,
and different exit designs.

manages_complexity:
Compellence collapses an unmanageable design problem — "how do I get a sovereign actor to
change policy?" — into a small set of slot-filling questions: what is the positive demand,
what continuing pressure is applied, what release condition will the target recognise, and
what exit preserves enough of the target's face to make compliance choosable? The
practitioner can then reason about each slot independently, identify which is the weak point,
and intervene there, rather than treating the whole campaign as an irreducible strategic
gestalt.

The decomposition also separates *coercion-theoretic* design questions from *operational*
ones. Whether to apply economic, military, or reputational pressure is one decision; whether
the pressure is being *used* compellently or deterrently is a different decision with
different success criteria. Keeping these separate prevents the characteristic confusion in
which an operational choice of instrument is mistaken for a structural choice of mode, or in
which a campaign judged failing on deterrence criteria is actually a compellent campaign
lacking a face-saving exit. The complexity the pattern manages is the complexity of
*designing coercion toward a positive action*, reduced to four slots plus the standing
caution that visible compliance, not raw pressure, is usually the binding constraint.

abstract_reasoning:
Compellence supports several characteristic moves. The *asymmetry argument*: compellence is
harder than deterrence by a structural margin, so symmetric scaling of pressure is the wrong
design, and the analyst should plan for longer timelines, larger costs, and more diplomatic
patience. The *face-saving move*: because visible compliance is the bottleneck, designing an
exit that lets the target appear to act for its own reasons often unblocks a compellent
campaign where escalating pressure would not.

Three further moves complete the toolkit. The *continuing-pressure requirement*: once
compellence begins, pausing or lifting the pressure prematurely undoes the campaign — the
opposite of deterrence, where the cost is reserved for the trigger event. The *sunk-cost
trap*: compellent campaigns generate the compeller's own sunk costs (deployed forces, broken
relationships, lost diplomatic capital) that produce continuation pressure independent of
strategic merit, so sunk-cost hygiene is a standing discipline. And the
*credibility-precommitment move*: tying-hands and burning-bridges signals make continuing
pressure more believable, the same move in international relations and in parenting, where a
parent who relents under tantrum pressure undoes future compellence. The reasoner asks, at
every turn: is this a positive demand or a prohibition, is the pressure continuing or
trigger-reserved, what release condition will the target recognise, and does a face-saving
exit exist that makes visible compliance choosable?

knowledge_transfer:
Compellence transfers across international relations, labor, regulation, debt collection,
ransomware, parenting, platform design, and hostage negotiation, but it transfers *as a
framed strategic concept* — the coercion-theory vocabulary, the normative load, and the
strategic-actor presupposition travel with it, which is what places it at the framed end of
the spectrum. The role mapping is consistent: the *positive demand* maps to missile
withdrawal, wage concessions, violation correction, payment, homework; the *continuing
pressure* maps to the blockade, the strike, the per-diem fine, the encryption, the withheld
privilege; the *release condition* maps to the target-identifiable threshold in each domain;
and the *face-saving exit* maps identically to the design feature that lets visible
compliance be chosen despite reputational cost.

The transfers are documented. Schelling's analytic vocabulary — continuing pressure, release
condition, face-saving exit — was imported into negotiation theory and used to redesign
strike endgames around face-saving employer-concession framings.<!-- FACT-D59-906 -->[^schelling-1966] The analysis of *why*
compellence is hard, that the target's compliance is publicly visible and reputationally
costly, transferred directly into the analysis of why public ransom payments encourage future
attacks while insurer-mediated payments do not.<!-- FACT-D59-907 -->[^hernandez-castro-etal-2020] Forced-action design in behavioural systems —
consent flows, upgrade-or-lose-features — is recognisably compellent and inherits the same
exit-design considerations. Per-diem regulatory penalties were refined once analysts noticed
they were not merely bigger one-shot fines but a different structural instrument with
continuing-pressure dynamics. And blocking access until a security challenge is passed is
compellent, with low-compliance-friction challenge design as the face-saving-exit move.<!-- FACT-D59-908 -->[^captcha-survey-2021] The
honest qualification is the strongest of any prime in this batch: compellence is heavily
human-practice-bound, normatively loaded, and institutionally rooted in coercion theory, so it
imports an interpretive frame into each new domain rather than being recognised as bare
structure — it is a sibling of deterrence under a coercion parent, and its cross-domain reach
is the reach of a named strategic instrument. The unifying transfer move is consistent:
identify whether a coercive instrument is being used compellently (continuing pressure for a
positive action) or deterrently (reserved cost against a proscribed action), then apply the
substrate-independent design considerations — continuing-pressure discipline, sunk-cost
hygiene, and face-saving exit — for the mode identified.

formal_abstract:
The 1962 Cuban Missile Crisis is the discipline's defining worked instance, and it maps the prime's slots exactly. The positive action-demand was withdrawal of the Soviet missiles already in Cuba<!-- FACT-D59-909 -->[^allison-zelikow-1999] — *do X*, not refrain from a future act, which is what made the episode compellence rather than deterrence. The continuing pressure was the naval quarantine, held live around the island rather than reserved against a trigger: lifting it prematurely would have undone the campaign, which is the continuing-pressure commitment in its pure form. The release condition was target-recognisable and explicit — verified removal of the missiles visibly terminates the blockade. The face-saving exit was the structurally decisive feature: the visible-compliance bottleneck (the Soviets had to back down first, publicly, by a deadline) was unblocked only when a face-saving exit was supplied in the form of a quiet, deniable reciprocal concession (the later withdrawal of comparable missiles elsewhere), letting compliance be chosen despite its reputational cost.<!-- FACT-D59-910 -->[^allison-zelikow-1999] The episode also demonstrates the prohibition-asymmetry invariant: a symmetrically scaled deterrent posture (threatening retaliation *if* missiles were used) would have been easier, because its success would have been an invisible non-event; compellence demanded visible, deadline-bound, reputationally costly action, which is exactly why the crisis turned on exit design rather than on escalating pressure. The diagnosis the prime enables: the binding constraint was never the magnitude of force the United States could bring, but the target's visible compliance — so the intervention was a face-saving exit, not more pressure.

**Mapped back:** The quarantine instantiates every slot — positive demand, continuing pressure, recognisable release, face-saving exit, visible-compliance bottleneck — and shows the asymmetry invariant in action: the campaign was unblocked by exit design, not by force magnitude, because compliance had to be visible.

applied_industry:
The same framed structure recurs in regulatory enforcement and in ransomware, two domains far from international relations. Per-diem regulatory penalties are a compellence engine: a continuing daily fine demands a *positive action* (correct the violation), the pressure is held live until compliance rather than levied once for a completed offence, the release condition is the inspector's verification that the fix is done, and the face-saving exit is often a negotiated compliance schedule that lets the firm act "on its own initiative" rather than under visible coercion. Analysts refined per-diem penalties precisely once they recognised these were not merely larger one-shot fines (which would be deterrence, punishing a completed act) but a structurally different instrument with continuing-pressure dynamics — the prime's clarity contribution made operational. Ransomware-by-encryption is the same instrument turned malicious: the positive demand is payment, the continuing pressure is the data held encrypted<!-- FACT-D59-911 -->[^young-yung-2017] (costs continue until the demanded act is performed), and the release condition is the decryption key. The prime's analysis of *why* compellence is hard transfers directly to the public-policy finding that visible ransom payments encourage future attacks — because compliance is publicly observable and reputationally legible — while insurer-mediated payments, which supply a kind of visibility-reducing exit, change the dynamics.<!-- FACT-D59-912 -->[^rusi-cyber-insurance-2021] A third instance, a software platform's forced upgrade (continuing feature degradation until the user updates), shows the same slots, with low-friction upgrade flows as the face-saving-exit move that converts grudging compliance into a chosen action.

**Mapped back:** Per-diem penalties, ransomware, and forced upgrades are all compellence — continuing pressure for a positive action, terminable at a recognisable release, made choosable by an exit — transferring as a framed strategic instrument whose binding constraint is visible compliance, not raw pressure.