On Background

core_idea: "On background" is the middle tier of the journalism attribution ladder, between on the record and off the record: information may be published, but the source may be identified only by a generic class descriptor — "a senior administration official," "a person familiar with the matter," "a Western diplomat" — and never by name or specific role. The structural commitment is a negotiated attribution boundary that separates the evidentiary content from the source identity. The published claim is freed; the source's identity remains shielded. The class descriptor performs a specific credibility-warrant function for the reader: it conveys that the speaker occupies a role or proximity appropriate to the claim (senior enough to know, involved enough to be reliable) without exposing the individual to retaliation or identification. The key design parameter is descriptor granularity — how precisely the class is named — which sets a noise-tolerance trade-off: a descriptor specific enough to carry genuine warrant ("a senior NSC official familiar with the arms-control negotiations") risks identifying the source if only a few people fit the description; a descriptor too generic ("a person with knowledge of the situation") empties the warrant of meaning. Three distinct breach modes follow from this: over-specific descriptor (source effectively identified), over-generic descriptor (warrant hollow and reader-misleading), and wrong-class descriptor (warrant misleading about positional authority). When publications over-rely on background attribution, the class descriptors proliferate until they lose discriminatory power — "senior administration official" fails to distinguish cabinet members from mid-level staff, and the warrant structure collapses. The on-background convention is closely paired with off the record: off the record prohibits publication entirely; on background permits publication under identity restriction. Diplomatic background briefings, corporate pre-announcement calls, qualitative-research pseudonymisation, and intelligence analytic attribution under redacted sourcing all instantiate the same content-versus-identity separation in adjacent professional contexts.

scope_of_application:
"On background" lives across the reporting contexts of journalism where a source is published under a class descriptor rather than by name — wherever the attribution ladder governs how a shielded source's claim is attributed; its reach is within that domain. The structurally identical content-versus-identity separations elsewhere — diplomatic background briefings under Chatham House Rule-style conventions, corporate pre-announcement calls and technology embargoes, qualitative-research pseudonymization, intelligence analytic products under redacted sourcing — are fellow instances of the general content-versus-identity-separation pattern (carried by `confidentiality`, `access_control`, `contract`, and `responsibility_attribution`, with the granularity knob a weak shadow of the privacy re-identification machinery), not uses of this journalism tier, so they are analogy and stay out of the map.

- **Political and government reporting** — the canonical home: "a senior administration official," "a person briefed on the matter," where the class descriptor warrants the source's proximity to the claim without naming them.
- **National-security and diplomatic reporting** — "a Western diplomat," "an intelligence official familiar with the assessment," shielding sources whose naming would carry severe consequences.
- **Business and financial reporting** — "a person familiar with the negotiations," "a Wall Street trader," conveying market-relevant positional authority under identity restriction.
- **Whistleblower and source-protected reporting** — anonymous-source protections functioning as on-background-at-publication, the descriptor carrying warrant while the identity stays shielded.
- **The attribution ladder as surrounding apparatus** — the middle tier between on the record and off the record (its sibling `off_the_record`), negotiated at the start of a source interaction across all beats.

structural_signature:
**Sig role-phrases:**

- **the publishable content** — the evidentiary claim freed for public use, the item the tier permits to appear
- **the shielded source identity** — the individual's name and specific role withheld, the restricted item separated from the content
- **the negotiated attribution boundary** — the explicit middle-tier license (between on the record and off the record) permitting publication under an identity restriction, so the question is how to attribute, not whether to run
- **the class descriptor** — the generic role label ("a senior administration official," "a person familiar with the matter") attached in place of the name
- **the credibility-warrant transfer** — the descriptor's evidentiary function, telling the reader the speaker holds a role or proximity adequate to the claim
- **the granularity knob** — how precisely the class is named, the single tunable parameter
- **the warrant-versus-identifiability trade-off** — precision buying warrant but spending source safety, generality protecting the source but emptying the warrant, with a usable band bounded at both ends
- **the three breach modes** — over-specific (source named by elimination), over-generic (warrant hollow, reader misled), wrong-class (warrant misrepresents positional authority)
- **the aggregate warrant collapse** — descriptors proliferating under overuse until "senior administration official" no longer discriminates, the warrant structure failing newsroom-wide before any single attribution looks wrong

what_it_is_not:
- **Not off the record.** Off the record bars publication of the content entirely; on background *permits* publication under an identity restriction. The reporter's question is therefore not "may I run this?" but "*how* may I attribute it?" — they are adjacent tiers of one ladder, differing in degree, and confusing them treats a permission as a prohibition.
- **Not full anonymity.** The content *is* published, and it carries an attribution — a generic class descriptor ("a senior administration official," "a person familiar with the matter") rather than a name. The source identity is shielded, not the claim, so this is a *restricted attribution*, not the absence of attribution that a bare anonymous tip would be.
- **Not decoration.** The class descriptor does real evidentiary work — a *credibility-warrant transfer* telling the reader the speaker holds a role or proximity adequate to the claim (senior enough to know, close enough to be reliable). "A senior NSC official familiar with the negotiations" is a warrant to be assessed (is this the right class of speaker for this claim?), not a throwaway gesture toward a hidden source.
- **Not "more generic is safer."** Descriptor granularity is a tunable knob with a *usable band bounded at both ends*: too specific and it names the source by elimination when only a few people fit; too generic and it empties the warrant, leaving the reader misled about how much to credit the claim. Defaulting to maximal vagueness is its own breach (over-generic), not a safe choice — and aggregate overuse drifts the whole descriptor vocabulary toward non-discrimination ("senior administration official" ceasing to separate a cabinet secretary from a mid-level aide).
- **Not data anonymization.** It is a *negotiated* attribution license between specific parties at a specific moment, not a data-processing operation that strips identity from a dataset. The granularity knob is a weak, qualitative *shadow* of the re-identification problem that data privacy formalizes (k-anonymity, differential privacy) — recognizable structure, but far thinner than the quantified machinery.
- **Not responsibility attribution.** Responsibility attribution assigns credit or blame; on background *restricts* source-identity attribution downstream in a publication. It is the dual concept — a constraint on naming who said it, not an allocation of who is answerable for it.

clarity:
Naming the on-background tier makes one separation legible above all: the split between a claim's *evidentiary content* (publishable) and its *source identity* (shielded), negotiated as an explicit attribution boundary rather than left to ad hoc anonymity. That clears up where on background sits relative to its neighbors on the ladder — it is not off the record, which bars publication outright, but a permission to publish *under an identity restriction* — so the reporter's question is no longer "may I run this?" but the sharper "*how* may I attribute it?" The frame also reveals what the generic class descriptor is actually for: it is not decoration but a *credibility-warrant transfer*, telling the reader that the speaker holds a role or proximity adequate to the claim (senior enough to know, close enough to be reliable) while withholding the name. Seen that way, the descriptor is doing evidentiary work for the reader, and "a senior administration official" can be evaluated as a warrant — is this the right class of speaker for this claim? — instead of read as a mere gesture toward a hidden source.

The decisive clarity is that the descriptor's *granularity* is a tunable parameter with a built-in trade-off, and naming it converts a vague worry about anonymous sourcing into a precise design question. Too specific a descriptor ("a senior NSC official familiar with the arms-control negotiations") can name the source by elimination when only a handful of people fit; too generic a one ("a person with knowledge of the situation") empties the warrant of meaning. Holding that trade-off in view splits what would otherwise look like a single "anonymous source problem" into three diagnosable breaches: over-specific (the source is effectively identified), over-generic (the warrant is hollow and the reader misled about how much to credit the claim), and wrong-class (the warrant misrepresents the speaker's positional authority). It further exposes a slow, aggregate failure invisible at the level of any one story: when a newsroom over-relies on background, the class descriptors proliferate until they lose discriminating power — "senior administration official" ceases to separate a cabinet secretary from a mid-level aide — and the warrant structure quietly collapses. The label lets an editor ask not just "is this source protected?" but "does this descriptor still carry warrant, and at what cost to the source's safety?"

manages_complexity: Sourcing under anonymity looks, untreated, like one amorphous "anonymous source problem" — a reporter weighing case by case whether to run an unnamed tip, how to phrase the attribution, whether the shielding is adequate, with no fixed handle on what is being traded against what. The on-background tier compresses that diffuse worry onto a single design parameter and a small branch structure. The first compression is locating the tier on the attribution ladder: on background is publication *under an identity restriction*, distinct from off the record (no publication), so the reporter's question collapses from "may I run this?" to the sharper "*how* may I attribute it?" — a difference of degree along a fixed scale rather than an open judgment. The second, decisive compression is recognizing that the generic class descriptor does evidentiary work — a *credibility-warrant transfer* telling the reader the speaker holds a role or proximity adequate to the claim — and that its *granularity* is a single tunable knob with a built-in trade-off: precision buys warrant but spends source safety, generality protects the source but empties the warrant. So the whole negotiation reduces to setting one parameter (how precisely to name the class) against one trade-off (warrant value versus identifiability), and the qualitative outcome reads off where that knob sits. That single parameter also fixes a clean three-way classification of what would otherwise be an undifferentiated "bad sourcing": *over-specific* (descriptor names the source by elimination), *over-generic* (warrant hollow, reader misled about how much to credit the claim), and *wrong-class* (warrant misrepresents the speaker's positional authority) — three diagnosable breaches, each tied to a specific setting or mis-setting of the granularity knob, rather than a vague sense that the attribution is off. The frame further exposes a slow aggregate failure invisible at the single-story level and makes it readable as the same parameter drifting in bulk: when a newsroom over-relies on background, descriptors proliferate and lose discriminating power — "senior administration official" ceases to separate a cabinet secretary from a mid-level aide — so the warrant structure collapses across the publication even when each individual descriptor looked acceptable. Instead of an open-ended anonymity problem, the practitioner tracks one ladder position, one granularity parameter, and one warrant-versus-safety trade-off, and reads off how to attribute, which of three breaches threatens, and whether the descriptor still carries warrant at acceptable cost — at the level of a single story and of the newsroom's aggregate practice alike.

abstract_reasoning:
With the negotiation reduced to one ladder position, one granularity knob, and one warrant-versus-safety trade-off, the tier licenses inferences keyed to the descriptor as a tunable credibility instrument.

*Diagnostic — evaluate the class descriptor as a warrant, and classify a sourcing failure by how the granularity knob is mis-set.* The signature inference treats the generic descriptor not as a gesture toward a hidden source but as a *credibility-warrant transfer* doing evidentiary work, and asks of it the warrant question: is this the right class of speaker for this claim — senior enough to know, close enough to be reliable? "A senior NSC official familiar with the arms-control negotiations" is read as a warrant to be assessed, not a hidden name to be guessed. From the single granularity parameter the analyst classifies any sourcing failure into one of three diagnosable breaches: *over-specific* (the descriptor names the source by elimination because only a handful fit), *over-generic* (the warrant is hollow and the reader misled about how much to credit the claim), and *wrong-class* (the warrant misrepresents the speaker's positional authority). Each maps to a specific setting or mis-setting of the knob, so "the attribution is off" resolves into which way it is off. A second-scale diagnostic reads an aggregate signature invisible in any one story: when descriptors proliferate until "senior administration official" no longer separates a cabinet secretary from a mid-level aide, the analyst infers a newsroom-wide warrant collapse from over-reliance on background, even where each individual descriptor looked acceptable.

*Interventionist — set the descriptor granularity to balance warrant against exposure, and predict the trade each setting makes.* The lever is the granularity knob, and the intervention is to set it against a built-in two-sided trade-off with a forecast for each direction: making the descriptor more precise buys warrant but spends source safety (predicted to raise identifiability when few people fit), while making it more generic protects the source but empties the warrant (predicted to leave the reader unable to gauge how much to credit the claim). The prescribed move is to find the granularity that carries genuine warrant at acceptable identification risk for the specific claim and source pool — neither maximizing precision nor defaulting to the safest vagueness. At the aggregate scale the intervention is to ration background attribution itself, on the prediction that overuse drifts the whole stock of descriptors toward non-discrimination regardless of any single story's care.

*Boundary-drawing — content is separated from identity, the tier sits between its neighbors, and the descriptor must clear a warrant floor.* The tier draws its defining boundary by splitting a claim's *evidentiary content* (publishable) from its *source identity* (shielded) as an explicit negotiated boundary, so the reporter's question is bounded away from "may I run this?" to "*how* may I attribute it?" Its position on the ladder bounds it against off the record (which bars publication outright) and on the record (named attribution): on background is publication *under an identity restriction*, a difference of degree along a fixed scale. The granularity parameter draws an inner boundary at both ends — below a precision floor the descriptor carries no warrant and ceases to do evidentiary work; above a precision ceiling it identifies the source and breaches the shield — so the usable band is bounded on both sides, and a descriptor outside it has failed the tier's purpose even if publication proceeded.

*Predictive — the descriptor's granularity predicts both source exposure and reader credence, at single-story and newsroom scale.* From where the granularity knob is set the analyst predicts two outcomes at once: how identifiable the source is (precise descriptors against a small eligible pool predict exposure) and how much warrant the reader receives (generic descriptors predict under-credence or misplaced credence). The construct also predicts the aggregate trajectory: sustained over-reliance on background is forecast to erode the discriminating power of the descriptor vocabulary across a publication, so the warrant structure is predicted to collapse in bulk before any single attribution looks wrong — a failure anticipated from the rate of background use rather than diagnosed story by story.

knowledge_transfer:
Within journalism the tier transfers *as mechanism*, intact, across the sourcing situations that use the attribution ladder. The content-versus-identity separation (the evidentiary claim freed, the source identity shielded behind a generic class descriptor), the reframing of the descriptor as a *credibility-warrant transfer* (assess "a senior NSC official familiar with the negotiations" as a warrant — is this the right class of speaker for this claim? — rather than as a hidden name to guess), the single tunable granularity parameter with its built-in warrant-versus-identifiability trade-off, the three breach modes (over-specific, over-generic, wrong-class), and the aggregate-scale failure (descriptor proliferation collapsing discriminating power across a newsroom) all carry without translation. A reporter who has internalized the background NSC briefing applies the *same instrument* to every class-descriptor attribution, reading off how to attribute, which breach threatens, and whether the descriptor still carries warrant at acceptable source-exposure cost — at the level of a single story and of the publication's aggregate practice alike. (It is the middle tier of one ladder with its sibling `off_the_record`: off the record bars publication entirely, on background permits publication under an identity restriction.)

Beyond journalism the honest account is a *shared-abstract-mechanism* one, and it tracks its sibling closely: on background factors into the same catalog primes as `off_the_record` — the broader normative class of confidentiality, `access_control` (the structural cousin governing access where this governs downstream *use* and *attribution*), `contract` and `commitment` (the license-as-agreement layer), and `responsibility_attribution` (the dual concept — here a *restriction* on source-identity attribution rather than the assignment of credit or blame). The same content-versus-identity separation recurs across adjacent professional contexts as genuine co-instances: diplomatic background briefings (Chatham House Rule-style conventions), corporate pre-announcement calls and technology embargoes, qualitative-research pseudonymization (quotes attributed to "a mid-career nurse manager, hospital A"), and intelligence analytic products with class-descriptor attribution under redacted sourcing. But what travels across these is the *general content-versus-identity-separation pattern and its constituent primes*, not the journalism tier; what stays home-bound is the on-background cargo — the journalism class-descriptor ladder, the attribution-rule conventions, the source-protection practices, the specific "senior administration official" vocabulary. So the cross-domain reasoner should carry the general pattern (and confidentiality, `access_control`, `contract`, `responsibility_attribution`), and treat a diplomatic background briefing or a research pseudonym as a fellow instance rather than as "on background"; using the journalism label across that boundary is analogy to be marked.

The standout transfer note is the *descriptor-granularity* parameter, which is itself a clean shared-abstract-mechanism case and shows exactly where the deeper portable lesson lives. The trade-off it encodes — a descriptor specific enough to carry genuine warrant risks identifying the source when only a few people fit; one generic enough to protect the source empties the warrant — is a recognizable *shadow* of the general re-identification problem formalized in data privacy as k-anonymity and differential privacy (and more broadly as pseudonymization): granularity of a quasi-identifier traded against re-identifiability of the individual. That structure genuinely recurs wherever an evidentiary contribution must be preserved while identity is blurred at a controlled granularity — but it recurs there in *full, quantified* form, while on background instantiates it in a much *weaker, qualitative* form bound to negotiated class descriptors. So the portable lesson at the granularity knob belongs to the general re-identification / privacy machinery, not to "on background," whose version is the journalism-specific, much-thinner realization. The tier stays distinct from its neighbors accordingly — it is not `off_the_record` (which prohibits publication, where this permits it under attribution restriction), not data-processing anonymization in the privacy sense (it is a *negotiated* attribution license between specific parties at a specific moment, not a data operation), and not `responsibility_attribution` in the credit/blame sense (it restricts *source-identity* attribution downstream). Strip the journalism idiom and what remains is the content-versus-identity-separation pattern carried by confidentiality, `access_control`, `contract`, and `responsibility_attribution`, with the granularity knob a weak shadow of the general re-identification structure — the boundary between this domain-specific abstraction and the substrate-independent mechanisms it composes (see *Structural Core vs. Domain Accent*).


Onboarding cliff

one_liner: Diagnose first-use abandonment as a geometry of two curves — cumulative cost crossing the user's willingness-to-invest before cumulative value crosses willingness-to-stay — separating first-contact complexity from steady-state complexity and naming exactly two levers.

status: draft

core_idea:
An onboarding cliff is the first-use failure mode in which the cumulative cost demanded of a new user before any payoff is delivered — in configuration steps, vocabulary acquisition, prerequisite credentials, sequential commitments, and elapsed time — exceeds the user's initial willingness to invest, causing abandonment before the user reaches the regime where the system delivers value. The structural failure is not that the system is deficient once mastered; it is that the cost curve at first contact is too steep relative to the value curve at first contact.

The geometry identifies the two independent levers: flatten the cost curve by deferring or eliminating cost-bearing steps, substituting sensible defaults for choices, and removing prerequisite gatekeeping; or accelerate the value curve by delivering visible payoff earlier in the sequence, so the user crosses a motivation-sustaining threshold before the cost accumulates to an abandonment point. The cliff is distinct from steady-state learning-curve difficulty: a system can have a shallow long-run learning curve yet an abandoning first-contact segment, and a system can be genuinely complex in steady state yet have a well-engineered first-contact curve. This separation — system complexity in steady state versus system complexity at first contact — is the concept's organizing distinction, and it maps to distinct product-analytics metrics (activation rate versus retention rate) and distinct design projects (onboarding flow redesign versus feature simplification).

scope_of_application:
The onboarding cliff lives across the first-use contexts of HCI, product, and UX design — wherever a first-time user with bounded initial motivation meets a multi-step system before any payoff is delivered; its reach stays inside that substrate, because the off-substrate analogues (immigrating, joining an organization, learning an instrument) share only the cost-outran-value shape and are carried by the general activation-threshold pattern, not by this name. Within the domain it also has a native analytics arm, where the cliff is the activation-rate failure read off product instrumentation rather than a retention problem.

- **Consumer software and SaaS.** Account, workspace, connector, query-language, and dashboard setup stack up before the first chart — the canonical case, where time-to-first-value instrumentation and the activation-versus-retention metric split live.
- **Home medical devices.** A patient must master vocabulary, calibration, and alarm configuration before the first dose, so a steep first-contact cost curve produces abandonment or unsafe workarounds.
- **Public-service and e-government flows.** Dozens of required fields, document uploads, and identity verifications accumulate before an eligibility answer is even returned, front-loading cost ahead of any payoff.
- **Education platforms.** Account creation, enrollment, plug-in install, and proctoring setup gate the first lecture, so learners abandon before reaching instructional value.
- **Control-room operator onboarding.** A new operator must absorb the alarm hierarchy, procedure index, and control schema before a routine shift is operable — the same first-contact cost wall in an operational interface.
- **Volunteer-organization onboarding.** Background checks, training modules, scheduling commitments, and policy acknowledgments precede the first activity, so prospective volunteers drop off before contributing.

structural_signature:
**Sig role-phrases:**

- **the deferred-payoff system** — a multi-step system whose value-delivery point is reached only after a sequence of configuration, learning, and commitment steps
- **the first-time user** — a novice with bounded initial motivation, attention budget, and trust
- **the cumulative cost curve** — front-loaded first-contact cost plotted against steps: configuration choices, vocabulary, prerequisite credentials, sequential commitments, elapsed time
- **the cumulative value curve** — visible payoff delivered against steps, the curve the cost must be outrun by
- **the two willingness thresholds** — willingness-to-invest (which cost must not cross first) and willingness-to-stay (which value must cross)
- **the cliff** — the failure: cost crosses willingness-to-invest before value crosses willingness-to-stay, causing abandonment before the value regime
- **the first-contact-versus-steady-state distinction** — the organizing split: first-use complexity and expert-mastery complexity move independently, routing the failure to activation (not retention)
- **the two independent levers** — the determinate remedy: flatten the cost curve (defer/eliminate steps, substitute defaults, drop gating) or steepen the value curve (deliver payoff sooner)
- **the HCI-bound cargo** — time-to-first-value instrumentation, progressive disclosure, OAuth instant-value flows, the activation/retention metric split; off-substrate only the parent activation-threshold lesson travels

what_it_is_not:
- **Not evidence that the product is too complex.** A low engagement number invites the reflex "simplify the product," but the cliff is a failure of the *first-contact* cost curve, not of steady-state complexity, and the two move independently. Simplifying the mature feature set leaves the first-use segment untouched and cannot move an activation number; the product can become no simpler to master yet far easier to start.
- **Not the long-run learning curve.** The cliff is the *first-segment* failure of a learning curve, not its overall slope. A system can have a shallow long-run learning curve yet abandon users at first contact; the question is whether the user reaches the curve's downward portion at all, not how steep that portion is once reached.
- **Not generic "friction."** The cliff is friction *concentrated in the first-use segment*, where cumulative cost outruns cumulative value before any payoff. Treating it as undifferentiated friction loses the two-curve geometry, the activation-versus-retention routing, and the exactly-two-lever remedy that make the symptom actionable.
- **Not a failure to withdraw support as competence grows.** That is premature fading — pulling away scaffolding too early. The cliff is the opposite-timed failure: not providing enough *early* payoff in the first place, so the user never reaches the regime where reducing support would even be appropriate.
- **Not sunk-cost retention.** Heavy prior investment *retains* users by trapping those who already committed; the cliff *prevents* investment from ever accumulating, losing users before commitment begins. It is the inverse failure mode, not a variant of the same one.
- **Not the general activation-threshold pattern.** The portable abstraction — an initial investment that must exceed willingness-to-invest before any payoff — recurs in joining an organization, immigrating, or learning an instrument, and is carried by the activation-threshold / learning-curve-initial-segment pattern. "Onboarding cliff" is the software first-use instance with its time-to-first-value instrumentation, progressive disclosure, and activation/retention metric split; the off-substrate analogues use different remedies entirely (mentoring, visa accommodations, pedagogic sequencing), so the name imports product machinery that does not fit there.

clarity:
Naming the onboarding cliff separates two measurements that a "users don't engage" finding silently conflates: *system complexity in steady state* — how hard the tool is for an expert who has already mastered it — and *system complexity at first contact* — how much a novice must absorb before any payoff arrives. The clarifying force is that these can move independently: a system with a shallow long-run learning curve can still abandon users at first contact, and a system that is genuinely intricate in steady state can have a well-engineered first-contact curve. Without the distinction, a low engagement number invites the wrong inference — "the product is too complex, simplify it" — when the failure may lie entirely in the *first segment* of the cost curve, untouched by simplifying the mature feature set.

That separation is what makes the symptom actionable, because it maps onto distinct measurements and distinct projects. The diagnostic it licenses is no longer "is this hard to use?" but "does cumulative cost cross the user's willingness-to-invest threshold *before* cumulative value crosses the willingness-to-stay threshold?" — a question about the relative geometry of two curves at first contact, which in turn names exactly two independent levers: flatten the cost curve (defer or eliminate steps, substitute defaults, drop prerequisite gating) or steepen the value curve (deliver visible payoff sooner). It tells the practitioner which number is failing (activation, not retention) and which redesign answers it (onboarding-flow reshaping, not feature simplification) — distinctions that the undifferentiated notion of "friction" or "the product is too complicated" cannot supply.

manages_complexity:
"Users don't engage" arrives as one undifferentiated number with a sprawling set of possible causes and an even larger set of candidate fixes — the product is too complex, the copy is unclear, there are too many fields, the value proposition is weak, the feature set is bloated, trust is low — and a team facing it can spend that budget anywhere, simplifying mature features that no novice ever reached. The onboarding cliff compresses that sprawl to a geometry: plot, against steps taken at first contact, a cumulative *cost* curve (configuration, vocabulary, prerequisites, sequential commitments, elapsed time) and a cumulative *value* curve, and the entire failure reduces to their relative shape — a cliff exists precisely where cost crosses the user's willingness-to-invest threshold before value crosses the willingness-to-stay threshold. The many-headed "why won't they engage" question collapses to one about two curves and two thresholds, and the diagnosis is read off that crossing rather than re-argued from the full list of suspected causes.

That reduction is what the analyst then tracks, and it is small. The cliff's location decomposes into a handful of engineerable quantities — time-to-first-value, prerequisite-sequence depth, decisions-before-payoff, mental-model surface, trust-cost — each a measurable segment of the cost curve rather than a vague property of the whole product. The two-curve picture also fixes the branch structure of the remedy: because only relative geometry matters, there are exactly two independent levers, flatten the cost curve (defer or eliminate cost-bearing steps, substitute defaults, drop prerequisite gating) or steepen the value curve (deliver visible payoff sooner), and any fix is one or the other or both. And the concept's organizing distinction — first-contact complexity versus steady-state complexity — partitions the problem space so the analyst reads off *which* number is failing and *which* project answers it: a cliff is an activation failure, not a retention failure, and its cure is onboarding-flow reshaping, not feature simplification, the two moving independently so that a steady-state-complex system can have a well-engineered first-contact curve and vice versa. The move is from a single opaque engagement deficit with an unbounded menu of explanations and fixes to a two-curve, two-threshold geometry tracked through a few cost-segment metrics, yielding a determinate two-lever remedy and a clean routing to the right metric and the right redesign — distinctions an undifferentiated notion of "friction" or "too complicated" cannot supply.

abstract_reasoning:
The onboarding cliff licenses a set of reasoning moves built on one geometric re-description — two cumulative curves, cost and value, plotted against steps taken at first contact — and the organizing distinction it forces between first-contact complexity and steady-state complexity.

*Diagnostic — read abandonment off the relative geometry of the two curves, and locate the cliff at the threshold crossing.* The characteristic inference plots cumulative cost (configuration, vocabulary, prerequisites, sequential commitments, elapsed time) and cumulative value against steps, then reads the failure as a property of where they cross the user's two thresholds. A cliff exists precisely where cumulative cost crosses the willingness-to-invest threshold *before* cumulative value crosses the willingness-to-stay threshold — so the diagnosis runs from "users abandon" to "the cost curve outran the value curve at first contact," a claim about relative shape rather than about the product's absolute difficulty. The load-bearing move is that only the *relative* geometry matters: a steep cost curve is not itself a cliff if value rises faster, and a modest one is a cliff if value lags. The analyst further localizes the abandonment to a specific cost segment — the connector step, the credential gate, the wall of definitions before payoff — by reading where the cost curve climbs steeply relative to where users drop, so the diagnosis names not just *that* there is a cliff but *which* segment is the edge.

*Diagnostic of which complexity is failing — separate activation from retention, and refuse the wrong inference.* The concept's sharpest diagnostic move is to split two measurements a low engagement number silently fuses: steady-state complexity (how hard the tool is for an expert who has mastered it) and first-contact complexity (how much a novice must absorb before any payoff). Because these move independently, the analyst infers from *where* in the lifecycle users are lost which complexity is at fault: drop-off before first value is an *activation* failure attributable to the first-contact curve; drop-off after sustained use is a *retention* failure attributable to steady-state difficulty. The crucial move is to *decline* the reflexive inference "engagement is low, so the product is too complex — simplify it," because simplifying the mature feature set leaves the first-contact segment untouched and cannot move an activation number. So a low engagement figure is read as a question — which threshold crossing failed, and at which lifecycle stage — not as an automatic mandate to reduce overall complexity.

*Interventionist — choose between exactly two levers, predict the effect of each, and match the project to the failing curve.* Because only relative geometry determines the cliff, the remedy space collapses to two independent levers, and the move is to reason about which one the geometry calls for. Flatten the cost curve — defer or eliminate cost-bearing steps, substitute sensible defaults for choices, drop prerequisite gating — and predict the cost crossing is pushed past the value crossing. Steepen the value curve — deliver visible payoff earlier in the sequence, reorder so a result arrives before the heavy steps — and predict the user clears a motivation-sustaining threshold before cost accumulates to an abandonment point. Each lever names the curve it reshapes, and the prediction is that reshaping the *first-contact* curve raises activation while leaving steady-state complexity untouched — so the product can become no simpler to master yet far easier to start. A fix aimed at feature simplification that fails to move activation localizes the error: the project addressed steady-state complexity when the cliff lived in the first segment.

*Boundary-drawing — separate the first-segment failure from the learning curve, from support-withdrawal, and from its inverse.* Several lines the concept draws. First, the onboarding cliff is the *first-segment* failure of a learning curve, not the curve's long-run slope: a system can have a shallow long-run learning curve yet an abandoning first-contact segment, so the move is to scope the diagnosis to whether the user reaches the curve's downward portion at all, not to how steep that portion is. Second, it is distinct from the failure to *withdraw* support as competence grows — the cliff is the failure to provide enough early payoff in the first place, so the user never reaches the regime where reducing support would be appropriate. Third, it is the inverse of retention-through-prior-investment: heavy prior investment *retains* users, whereas the cliff *prevents* investment from ever accumulating, so the move is to distinguish a system that traps committed users from one that loses users before commitment begins. These boundaries keep the diagnosis from sprawling into the undifferentiated notion of "friction," reserving it for friction concentrated in the first-use segment where cost outruns value before payoff.

knowledge_transfer:
Within HCI and product design the concept transfers *as mechanism*, intact. The two-curve geometry (cumulative cost against cumulative value at first contact, with a cliff where cost crosses willingness-to-invest before value crosses willingness-to-stay), the first-contact-versus-steady-state distinction, the activation-versus-retention routing, and the exactly-two-levers remedy (flatten the cost curve; steepen the value curve) carry without translation across every multi-step first-use system: home medical devices (a patient mastering vocabulary, calibration, and alarm config before the first dose), public-service and e-government flows (dozens of fields, uploads, and identity checks before an eligibility answer), education platforms (account, enrollment, plug-in, proctoring setup before the first lecture), control-room operator onboarding (alarm hierarchy, procedure index, control schema before a routine shift), consumer SaaS (account, workspace, connector, query language, dashboard before the first chart), and volunteer onboarding (background checks, training, scheduling, policy acknowledgment before the first activity). The engineerable cost segments (time-to-first-value, prerequisite-sequence depth, decisions-before-payoff, mental-model surface, trust-cost) and the standard remedies (progressive disclosure, lazy default configuration, sequenced tutorials, zero-config trials, instant-value demos) travel with the diagnosis, because all of these are the same substrate — a first-time human user with bounded initial motivation meeting a multi-step interface before payoff. This is genuine within-domain mechanism transfer.

Beyond that substrate the case is the third category: the same *shape* of failure recurs across domains, but the structural force lives with the parent prime, and this entry's own machinery stays home. The portable abstraction is an *activation threshold* — an initial investment that must exceed willingness-to-invest before any payoff is reached, below which engagement never begins — closely tied to the initial segment of `learning_curve_effects` and to the activation-energy idea (the energy threshold above which a reaction proceeds, of which the onboarding cliff is the user-experience analogue). That genuinely recurs as co-instances: joining a new organization, immigrating to a new country, taking up a musical instrument, adopting a new agricultural practice — each a step-function of front-loaded cost before benefit. But in those substrates the cross-domain lesson should be carried by the activation-threshold / learning-curve-initial-segment pattern, *not* by "onboarding cliff" as named, because the entry's distinctive cargo — time-to-first-value instrumentation, progressive disclosure, OAuth-driven instant-value flows, the activation-versus-retention metric split — is HCI/product furniture, and the substrate's own analogues of the *remedy* are different tooling entirely (mentoring, visa-interview accommodations, pedagogic sequencing, agricultural extension services). So to call a new immigrant's front-loaded burden an "onboarding cliff" borrows the cost-outran-value-at-first-contact shape while importing product-analytics machinery that does not fit; the honest move is to route the structural lesson to the activation-threshold prime and reserve the name for the software first-use case. (Neighboring boundaries reinforce this: the cliff is the *first-segment* failure of a learning curve, not its long-run slope; it is the failure to provide early payoff, distinct from `fading`'s premature withdrawal of support; and it is the inverse of sunk-cost retention, which traps users who already invested rather than losing them before investment begins.) The shape travels widely; the structural force and the named remedies do not — exactly the split drawn in *Structural Core vs. Domain Accent*.


Ontological Paradox

one_liner: Assess a self-causing closed causal loop — an object or piece of information that exists with no origin traceable outside the loop — by testing whether it is self-consistent (coherent, unlike the grandfather paradox) yet still lacking a traceable origin.

origin_domain: philosophy

core_idea: The ontological paradox (also called the bootstrap paradox or causal-loop paradox) is the puzzle structure that arises when an object, piece of information, or causal sequence exists in a self-consistent closed loop with no origin point traceable outside the loop — the artifact, in effect, causes its own existence. The structural commitment is that causal closure under self-consistency, formalized in physics as Novikov's self-consistency principle, is logically coherent in that no contradiction is generated within the loop, yet ontologically disturbing in that the question "where did this come from?" has no answer except "from itself." In the canonical philosophical example, a time traveler carries a musical score back in time and gives it to the composer who then publishes it as their own work; the score is performed, recorded, and eventually retrieved by the same traveler — the score exists in a closed loop with no moment at which anyone composed it from scratch, so its information content has no traceable origin event. In the physics of closed timelike curves, which Gödel's rotating-universe solution and Thorne's traversable-wormhole geometries permit in principle, Novikov self-consistency is the constraint that prevents the logical contradiction of the grandfather paradox (where the loop is self-undermining): a bootstrap loop is self-consistent (nothing prevents the loop from closing) but leaves the thermodynamic cost of the contained information unaccounted for. The paradox is precisely delineated from its consistency-violating sibling: a grandfather paradox closes a loop that prevents the loop from having started, producing a logical contradiction; an ontological paradox closes a loop that enables its own continuation, producing no contradiction but an inexplicable origin. In philosophy of causation it is used to probe whether a causal order is a necessary feature of reality or merely a contingent regularity of non-looping spacetimes, and in narrative theory it functions as a structural device for plots in which the traveler is their own progenitor.

scope_of_application:
The ontological paradox lives within the formal and conceptual analysis of self-referential causal structure — the metaphysics of causation and time, the physics of closed timelike curves, and information theory on causal loops, which together form one substrate, not a span of disciplines. Its reach is bounded there; the thinner self-reference/fixed-point structure it instantiates travels under its parent primes, and its fictional uses are illustrative analogy, so both stay out of this map.

- **Metaphysics of time and causation** — the central toy case (Mellor, Lewis, Sider) for adjudicating whether causal loops are coherent and whether causal order is a necessary or merely contingent feature of reality.
- **Physics of closed timelike curves** — the loops Gödel's rotating universe and Tipler–Thorne wormhole geometries permit, where Novikov self-consistency forbids the self-undermining grandfather form while allowing the self-enabling bootstrap form.
- **Quantum computation on CTCs** — Deutsch's consistency model, whose computationally interesting fixed-point solutions on closed timelike curves draw bootstrap-style ontological objections.
- **Information theory on causal loops** — the question of where the Shannon entropy of bootstrapped content comes from when no creation event injected it, the thermodynamic ledger the consistency constraint leaves open.
- **Narrative theory** — a recognized structural device for closed-loop, own-progenitor plots (Heinlein's *All You Zombies*, *Predestination*, *12 Monkeys*), used illustratively rather than as a transferred mechanism.

structural_signature:
**Sig role-phrases:**

- **the closed causal loop** — a causal chain in time with no origin event traceable outside the loop
- **the looping content** — the object, information, or sequence that the loop carries (the musical score, the progenitor traveler) and that, in effect, causes its own existence
- **the fixed-point structure** — the content is a fixed point of the pastward-information map: a solution of x = f(x), where f is "what reaches the past from the future"
- **the self-consistency** — closing the loop generates no contradiction; the loop is logically coherent (the constraint Novikov's principle enforces)
- **the consistency-preserving cut** — the discriminating feature: the bootstrap loop *enables* its own continuation, distinguishing it from the grandfather loop, which *prevents* its own initiation and so carries a genuine contradiction
- **the missing traceable origin** — the residual problem: "where did this come from?" has no answer except "from itself" — coherence without an initialization event
- **the unsettled thermodynamic ledger** — the further discard: self-consistency forbids contradiction but never accounts for the creation cost of the bootstrapped information, a separate ledger the constraint leaves open

what_it_is_not:
- **Not the grandfather paradox.** This is the consistency-*preserving* sibling, not the consistency-*violating* one. The grandfather loop closes in a way that prevents its own initiation, generating a genuine contradiction; the bootstrap loop closes in a way that *enables* its own continuation, generating none. They sit on opposite sides of the consistency cut.
- **Not a logical contradiction.** Nothing inconsistent is derived inside the loop, so it cannot be dismissed on logical grounds; the disturbance is *ontological*, not logical. What it lacks is not coherence but a *traceable origin* — the question "where did this come from?" has no answer except "from itself."
- **Not ruled out simply because it involves time travel.** Lumped under "time-travel oddities" the bootstrap loop inherits an air of impossibility it does not earn: if closed timelike curves are permitted at all, a self-consistent bootstrap loop is coherent. It is the genuinely disturbing-but-allowed case, not the excluded one.
- **Not feedback or circular causality.** Those are self-influencing structures that run *forward* in time, each cycle following the last; the ontological paradox closes the loop *in time itself*, with no external initialization event. Forward-running self-influence has an origin; the bootstrap loop does not.
- **Not every self-reference.** It is specifically a self-referential *causal/temporal* loop. A self-referential sentence (Quine's, the liar) is logical self-reference with no causal closure in time; the ontological paradox requires content that, in effect, causes its own existence.
- **Not resolved by Novikov self-consistency.** The self-consistency principle forbids the contradictory (grandfather) loops and permits the coherent (bootstrap) ones — but a coherence proof is not a complete account. It never supplies the missing origin nor balances the thermodynamic/informational ledger of the bootstrapped content, which remains unpaid by any event inside the loop.

clarity:
Naming the ontological paradox makes a fine but decisive distinction legible: a closed causal loop can be either *consistency-violating* or *consistency-preserving*, and only the former carries a logical contradiction. Lumped together with the grandfather paradox under the loose heading "time-travel oddities," self-causing loops inherit the grandfather's air of outright impossibility; the label pulls them apart. The grandfather loop closes in a way that prevents itself from ever having started — a genuine contradiction that rules the scenario out. The bootstrap loop closes in a way that *enables* its own continuation: nothing internal to it is contradictory, so it cannot be dismissed on logical grounds. What it lacks is not consistency but a *traceable origin* — and isolating that lack as the residual problem is exactly what the concept clarifies. The disturbance is ontological, not logical.

This sharpens the practitioner's question from "is this coherent?" to "is the loop self-consistent, and if so, where does its contained content come from?" In the metaphysics of causation, that lets one ask precisely whether causal order — every effect having a cause traceable outside itself — is a *necessary* feature of reality or merely a contingent regularity of non-looping spacetimes, since a self-consistent bootstrap loop is the clean case in which causal order fails without contradiction. In the physics of closed timelike curves, it identifies what Novikov self-consistency does and does not buy: the principle forbids the self-undermining (grandfather) loops while permitting the self-enabling (bootstrap) ones, so a candidate spacetime can be coherent yet still leave the thermodynamic cost of its bootstrapped information unaccounted for — a separate ledger the consistency constraint never settles.

manages_complexity: The metaphysician of time, the relativist studying closed timelike curves, and the narrative theorist each meet what looks like a fresh puzzle every time a causal loop appears: a musical score performed before anyone composed it, a protagonist who is their own progenitor, the information in a Deutsch fixed-point computation on a closed timelike curve, the object handed back to the past that was only ever obtained from the future, Gödel's rotating-universe and traversable-wormhole geometries that permit such loops in principle. Treated case by case, each tempts the same flat reaction — "time travel, therefore impossible" — and each seems to demand its own ruling on coherence. The ontological paradox compresses this whole class by reducing the assessment of any closed causal loop to two ordered questions whose answers fix the verdict. First: is the loop self-consistent — does closing it generate a contradiction, or not? That single parameter sorts every such puzzle into the two branches that organize the field. A loop that closes in a way preventing itself from ever having started — the grandfather form — carries a genuine logical contradiction and is ruled out; this is the branch Novikov self-consistency is built to forbid. A loop that closes in a way *enabling* its own continuation — the bootstrap form — generates no contradiction and cannot be dismissed on logical grounds at all. For loops that fall on this consistency-preserving branch, the second question is forced: does the loop's contained content have an origin traceable outside it? Here the answer is uniformly no, and isolating that "no" as the entire residual problem is the compression's payoff — the disturbance is relocated from logic to ontology, a missing origin rather than an incoherence. The analyst no longer re-litigates each self-causing artifact from its narrative or physical particulars but reads the outcome off the consistency bit and, on the coherent branch, off the origin question: contradiction and exclusion on one side; coherence-without-traceable-origin on the other, with the further recognition that the thermodynamic cost of the bootstrapped information remains a separate ledger the consistency constraint never settles. A scatter of seemingly distinct time-loop puzzles becomes one two-step diagnosis with a fixed branch structure, the qualitative verdict following from which side of the consistency cut a loop falls on rather than from the surface details of the artifact that loops.

abstract_reasoning:
The paradox equips the metaphysician and the relativist with a sequence of reasoning moves for adjudicating any proposed causal loop, all hinging on the consistency cut it draws. The first is *boundary-drawing by self-consistency*. Presented with a candidate loop, the analyst asks whether closing it generates a contradiction — whether the loop closes in a way that prevents its own initiation (grandfather form) or in a way that enables its own continuation (bootstrap form). This is the regime test: a loop on the grandfather side is ruled out on logical grounds alone, while a loop on the bootstrap side survives as coherent and cannot be dismissed by any appeal to contradiction. Reasoning from the form of the closure to the verdict is what lets the analyst exclude self-undermining spacetimes (the work Novikov self-consistency is built to do) while declining to exclude self-enabling ones.

The second is a *diagnostic, residual-problem move* applied on the coherent branch. Once a loop is found self-consistent, the analyst asks where its contained content — the score, the object, the information — has an origin traceable outside the loop, and reasons from the uniform answer "nowhere" to the precise nature of the disturbance: not an incoherence to be resolved but a missing origin event to be acknowledged. The signature here is that consistency is present yet origin is absent; recognizing that combination relocates the problem from logic to ontology and tells the analyst that no further internal inspection of the loop will produce the origin, because there is none to find.

The third is *predictive ledger-tracking*. The analyst predicts that self-consistency, even when fully established, leaves a separate account unsettled: the thermodynamic and informational cost of the bootstrapped content is never paid by any event inside the loop, so a spacetime can satisfy every consistency constraint and still carry information whose creation cost is unaccounted for. This licenses a sharp prediction about the limits of the consistency principle — it forbids contradiction but does not supply origins or balance information ledgers, so a coherence proof must not be mistaken for a complete account of where the loop's content came from.

The fourth is an *order-of-assessment move* that fixes the sequence in which a loop must be judged: consistency first, origin second. The analyst reasons that the consistency question is prior and decisive — it alone can rule a loop out — and that the origin question only becomes live, and only ever returns the answer "from itself," once consistency has been granted. Settling these in the wrong order conflates the bootstrap loop's mere strangeness with the grandfather loop's outright impossibility; taking them in order separates the loop that is excluded by contradiction from the loop that is merely without traceable beginning, which is the whole discriminating payload the concept carries within its home domain.

knowledge_transfer:
Within the formal analysis of causation, time, and self-reference the ontological paradox transfers *as a working diagnostic*, and its two-step assessment (consistency cut first, traceable-origin question second) carries across the substrate's subfields without translation. In **the metaphysics of time and causation** (Mellor, Lewis, Sider) it is the central toy case for adjudicating whether causal loops are coherent and whether causal order is necessary or contingent. In **the physics of closed timelike curves** (Gödel's rotating universe, Tipler–Thorne wormhole geometries, Deutsch's CTC-consistent computation) it is precisely what Novikov self-consistency is built to manage — forbidding the self-undermining grandfather loops while permitting the self-enabling bootstrap ones — and the residual-origin and thermodynamic-ledger observations apply directly to candidate spacetimes. In **information theory on causal loops** it sharpens the question of where the Shannon entropy of bootstrapped content comes from when no creation event injected it. These are genuinely one substrate — the formal/conceptual analysis of self-referential causal structure — so the diagnostic's reach across them is literal, not analogical.

Beyond that substrate the transfer splits, and honesty requires marking both halves. The narrative-theory and speculative-fiction uses (Heinlein's *All You Zombies*, *Predestination*, *12 Monkeys*, the looping artifact handed back to its own past) are *illustrative analogy* (case A): the bootstrap shape is borrowed as a plot device, but no mechanism transfers — the story dramatizes the puzzle rather than instantiating a physical or formal causal loop. What *does* genuinely recur, and is the honest cross-domain carrier (case B), is the thinner structure the paradox instantiates: *a closed loop whose content is a fixed point of the map that feeds it, self-consistent yet without an initialization traceable outside the loop.* That structure is already housed in the parent primes — `self_reference` (a structure referring to itself), `fixed_point` (the loop's content as a solution of x = f(x)), `feedback` / `circular_causality` (self-influencing causal structure, though these run forward in time rather than closing it), all under the umbrella `paradox`. Through the `fixed_point` parent the *consistency-preserving versus consistency-violating* distinction the concept teaches does reach real non-temporal cases — debugging any self-referential specification where "what initialized this?" must be answered: compiler bootstrapping, self-hosting language toolchains, fixed-point algorithms. But there the work is done by the fixed-point and self-reference primes, not by "ontological paradox" as named; the eponymous concept's home-bound cargo is the *temporal-causal* reading (a loop closed in time itself, with its grandfather sibling and its Novikov-self-consistency physics), which is causation-and-time furniture that does not and should not travel as a unit (see *Structural Core vs. Domain Accent*).


Open Availability

one_liner: Make a knowledge resource reachable by anyone under explicit, non-restrictive, machine-operative terms so that reuse shifts from negotiate-per-use to consult-the-license, unlocking combinatorial composition across an ecosystem.

core_idea:
Open availability is the governance posture in which a knowledge resource — an ontology, a dataset, a software package, a specification, a publication — is made accessible to any user under explicit and non-restrictive use conditions, converting the resource from a gatekept or implicitly-available asset into one with known, permissive terms that support downstream reuse, redistribution, and combination without per-use negotiation.

The pattern has four commitments that travel together. *Findability* means the resource can be discovered through a public lookup mechanism — a registry, a repository, a search index — without requiring prior knowledge of its existence or a relationship with the publishing group. *Accessibility* means the resource can be retrieved by any interested party without submitting a separate permission request for each use: the bits are reachable through an open channel. *Explicit use terms* means a license or open-access declaration accompanies the resource, specifying what holders of the resource are and are not permitted to do with it — and making that specification machine-readable and legally operative rather than implied or informal. *Non-restrictiveness* means the terms actually permit substantive reuse: machine reading, redistribution, modification, and incorporation into derivative works. The first three commitments without the fourth produce nominal openness; a resource that exists in a public repository under a license that prohibits most reuse is technically findable and accessible but not openly available in the sense that matters for downstream composition.

The pattern is operationalised across several knowledge-resource governance regimes that converge on the same four-part architecture for different substrates. The OBO Foundry's open-availability principle requires biomedical ontologies to carry explicit licenses permitting cross-ontology composition. The FAIR data principles (Findable, Accessible, Interoperable, Reusable) formalise three of the four commitments for research datasets. The Open Source Initiative's Open Source Definition codifies them for software. The Budapest, Bethesda, and Berlin declarations operationalise them for research publications. The Creative Commons license family was explicitly designed to port the GPL-style open-software architecture into other knowledge-resource media.

What these instantiations share structurally is the move from *negotiate-per-use* coordination to *consult-the-license* coordination. In a closed or ambiguously-licensed resource ecosystem, every potential reuse requires a transaction with the rights holder: identifying who holds the rights, reaching them, describing the intended use, awaiting permission, and absorbing any conditions imposed. At population scale — thousands of researchers, dozens of ontologies, millions of datasets — this per-use transaction cost is prohibitive and combinatorial reuse becomes effectively impossible. Explicit permissive licensing pre-authorises the full class of non-commercial or modification uses, reducing per-use coordination cost to near zero. The network consequence is that ecosystems of openly available resources can develop combinatorial compositions — ontologies that import other ontologies, datasets that join other datasets, tools that build on other tools — that closed ecosystems cannot, because the licensing is compatible and the permission is already granted.

The recurring failure mode the pattern guards against is nominal availability without substantive openness: a resource published in a public location under terms so vague, restrictive, or incompatible with other resources that practical reuse is blocked. OBO Foundry curation practice names this explicitly, requiring not just that terms exist but that they are unambiguous and permissive enough to enable the downstream composition the resource is intended to support.

scope_of_application:
Open availability lives within knowledge-resource governance; its reach is bounded to that domain, because its substance is one coordination posture applied to non-rivalrous knowledge resources, and the commons cases that share the word "open" (a forest, the airwaves) belong to a different prime family (`commons`, `tragedy_of_the_commons`) where the resource is rivalrous and the failure mode is overuse, not gated reuse. The exportable coordination move (`license_as_coordination`) is the parent's to carry. Within the domain the identical four-part architecture is instantiated across these substrates.

- **Biomedical ontologies** — the OBO Foundry open-availability principle requires ontologies to carry explicit licenses permitting cross-ontology composition and downstream tool development (Gene Ontology, Human Phenotype Ontology).
- **Research data** — the FAIR principles (Findable, Accessible, Interoperable, Reusable) formalize three of the four commitments for scientific datasets.
- **Open-source software** — the OSI Open Source Definition codifies the use-terms commitment, with source-code availability formalizing retrieval.
- **Open-access publishing** — the Budapest, Bethesda, and Berlin declarations operationalize the architecture for research publications.
- **Open standards** — W3C, IETF, and ISO open-standards practice opens specification documents and reference implementations to public use.
- **Open government data** — public-data portals (data.gov, the EU Open Data Portal) extend the posture to administrative records.

structural_signature:
**Sig role-phrases:**

- **the knowledge resource** — the ontology, dataset, software package, specification, or publication whose governance is at issue
- **the findability commitment** — discoverability through a public lookup (registry, repository, index) without prior knowledge or a relationship with the publisher
- **the accessibility commitment** — retrievability through an open channel without a separate per-use permission request
- **the explicit-terms commitment** — a machine-readable, legally operative license or open-access declaration stating what holders may and may not do, rather than implied or informal terms
- **the non-restrictiveness commitment** — terms that actually permit substantive reuse (machine reading, redistribution, modification, derivative works), the fourth commitment without which the first three yield only nominal openness
- **the three-layer stack** — the technical (where the bits live), legal (what the license permits), and social (whether the community treats it as usable) layers a breakdown localizes to
- **the consult-the-license coordination move** — the engineered payoff: pre-authorizing the whole class of intended uses converts negotiate-per-use into consult-the-license, dropping per-use cost toward zero
- **the combinatorial reach versus enclosure risk** — the population-scale consequence: compatibly licensed resources compose (ontologies importing ontologies, datasets joining datasets), against the standing risk that re-closure breaks everything built atop a resource

what_it_is_not:
- **Not mere availability.** "The resource exists somewhere a user could reach it" is exactly what open availability is *not*: the concept exists to separate availability from reachability-by-anyone-under-explicit-non-restrictive-terms. A maintainer who posts an ontology at a public URL and declares it "available" has not achieved open availability if downstream composition fails for want of operative, permissive terms — the failure mode the concept names *nominal availability without substantive openness*.
- **Not "free of charge."** The pattern is about *use terms*, not price: the load-bearing question is whether holders may machine-read, redistribute, modify, and incorporate the resource, not whether they paid for it. A paywall is one access barrier, but a gratis resource under terms that forbid reuse is still not openly available, and a priced resource is a separate axis from the licensing posture the concept governs.
- **Not satisfied by findability, accessibility, and a license alone.** The first three commitments without the fourth — *non-restrictiveness* — produce only nominal openness: a resource that is discoverable, retrievable, and licensed, but under terms prohibiting substantive reuse, is technically findable yet useless for composition. The fourth commitment, that the terms actually permit reuse, is what makes openness substantive rather than apparent.
- **Not the same as transparency.** Transparency concerns *disclosure* — the visibility of processes and decisions to stakeholders; open availability concerns *accessibility-for-use* of a resource under explicit terms. The two often co-occur, but their structural commitments differ: a resource can be fully disclosed yet encumbered by a license that blocks reuse, so transparency does not entail composability.
- **Not "open access" to a commons.** "Open access to a forest" or "to the airwaves" is a different problem entirely: those are *commons-management* situations governed by `commons` and `tragedy_of_the_commons`, where the resource is rivalrous and the failure mode is *overuse*. Open availability concerns non-rivalrous knowledge resources whose failure mode is *gated reuse*; the shared word "open" hides that the two belong to different prime families.

clarity:
Naming open availability separates two things that "the resource is available" silently fuses: *availability* (the resource exists somewhere a user could in principle reach) from *open availability* (it is reachable by anyone under explicit, non-restrictive terms). Without the distinction, a knowledge-resource maintainer can announce that an ontology or dataset is "available," point to a public URL, and believe the coordination job is done — while downstream composition quietly fails because the terms are vague, the license is incompatible, or reuse demands a permission request the maintainer never anticipated. The concept makes the failure mode visible and gives it a name: *nominal availability without substantive openness*, the resource that sits in a public repository under terms that block the very reuse it was meant to enable. The sharper question a curator can now ask is not "is this published?" but "is this composable — can a stranger machine-read it, redistribute it, and fold it into a derivative work without negotiating with me first?"

The concept also pulls apart three layers that ambiguous practice runs together: the *technical* layer (where the bits live and how they are served), the *legal* layer (what the license actually permits a holder to do), and the *social* layer (whether the community treats the resource as freely usable in practice). A resource can pass on one and fail on another — served from an open endpoint but encumbered by an incompatible license, or permissively licensed but undiscoverable for want of a registry entry — and localizing the breakdown to the right layer tells the maintainer which fix moves the needle, since a better server cannot cure a restrictive license and a permissive license cannot cure a missing lookup mechanism. Most pointedly, it reframes licensing from boilerplate into a coordination instrument: by reading "explicit permissive terms" as the move from *negotiate-per-use* to *consult-the-license*, the curator can see why combinatorial reuse at population scale stands or falls on whether the fourth commitment — non-restrictiveness — is actually met, not merely whether the first three create the appearance of openness.

manages_complexity: A reuse decision in a closed resource ecosystem is, in full, a thicket of bespoke transactions: for every ontology, dataset, or package a stranger might fold into a derivative, identify the rights holder, reach them, describe the use, await terms, and absorb conditions — a per-pair cost that grows combinatorially as the ecosystem scales to thousands of resources and users. Open availability collapses that thicket onto the license. Once a resource carries explicit, permissive terms, the entire class of intended uses is pre-authorised, so the cost of any given reuse drops to "consult the license" and the curator no longer reasons resource-by-resource and holder-by-holder. The whole posture reduces to four readable commitments — findability, accessibility, explicit terms, non-restrictiveness — checked once per resource; whether combinatorial composition is feasible across a population of resources then follows almost entirely from whether their licenses are present and compatible, not from re-litigating each pairing. A maintainer asking "will a stranger be able to build on this?" reads the answer off those four checks plus license compatibility, and a curator diagnosing a stalled composition localizes the break to the technical, legal, or social layer rather than auditing every downstream attempt. A coordination problem that is in principle quadratic in the number of resources is thereby compressed into a small per-resource checklist whose outcome predicts the ecosystem's combinatorial reach.

abstract_reasoning:
Reduced to a four-commitment checklist over a three-layer stack, open availability licenses the inferences a curator or resource maintainer draws when reasoning about reuse, all turning on the gap between nominal and substantive openness.

*Diagnostic — localize a stalled composition to a failed commitment or layer.* When a downstream composition fails — a stranger cannot fold an ontology into a derivative, a dataset will not join another, a tool cannot build on a library — the curator does not treat it as a generic "it didn't work" but infers *which* of the four commitments is missing and *which layer* it lives on. A resource that is reachable and licensed but absent from any registry has failed *findability* at the technical/social layer; one that is discoverable but demands a per-use permission request has failed *accessibility*; one that is served openly but carries no operative license has failed *explicit terms* at the legal layer; one that has all three yet sits under terms that forbid machine reading, redistribution, or modification has failed *non-restrictiveness* — the signature of *nominal availability without substantive openness*. The inference runs from the surface symptom (composition blocked) to the precise hidden defect, and it is sharp because the four commitments fail independently and a resource can pass three while silently failing the fourth.

*Interventionist — fix the layer that is actually broken, predict the change in reach.* Because the breakdown is localized, the remedy is too, and the concept predicts that a fix aimed at the wrong layer moves nothing. A better server or faster endpoint cannot cure a restrictive license; a permissive license cannot cure a missing registry entry; relicensing to permit modification and redistribution is predicted to *unlock* the class of compositions that the old terms foreclosed, while merely re-hosting it is not. The high-leverage intervention is therefore on the *fourth* commitment — converting terms from gatekept or ambiguous to explicit-and-permissive pre-authorises the whole class of intended uses at once, dropping per-use coordination cost toward zero and predicting a step change in how many strangers can build on the resource without negotiating. Each candidate fix is thus a prediction about *combinatorial reach*: relax the binding constraint and the feasible composition space expands; touch a non-binding layer and it does not.

*Boundary-drawing — decide whether a resource is composable, and whether two are combinable.* The concept gates a class of reuse inferences. A resource that passes all four checks may be treated as composable — a stranger can machine-read, redistribute, and incorporate it without per-use negotiation — and may be planned into derivative work; one that fails any check cannot be, and a maintainer's announcement that it is "available" does not license the assumption. A second, pairwise boundary governs *combination*: even two individually open resources compose only if their licenses are mutually *compatible*, so the curator reasons not just per-resource but per-pair, and an incompatible-license verdict forecloses the join regardless of each resource's standalone openness. The judgment "is this published?" is replaced by the operative "is this composable, and compatible with what I want to combine it with?"

*Predictive — combinatorial reach and enclosure risk at population scale.* From the per-resource checklist plus license compatibility, the curator predicts ecosystem-level outcomes no single resource exposes: ecosystems of openly available, compatibly licensed resources will develop combinatorial compositions — ontologies importing ontologies, datasets joining datasets, tools stacking on tools — that closed or incompatibly licensed ecosystems cannot, because the per-use permission is already granted and the cost is near zero. The same frame names the standing downside risk — *enclosure*: an openly available resource can later be re-closed, and because downstream compositions depend on its terms holding, the curator treats the durability of the open terms (and the social and legal machinery that resists re-closure) as load-bearing, predicting that re-enclosure of a widely-composed-upon resource propagates breakage through everything built on it.

knowledge_transfer:
Within knowledge-resource governance — the home domain — open availability transfers *as mechanism* across substrates that share the four-part architecture, because the cargo is one coordination move: convert *negotiate-per-use* into *consult-the-license* by attaching explicit, non-restrictive, machine-operative terms to a findable, retrievable resource. It is instantiated, with the same skeleton, across biomedical ontologies (the OBO Foundry open-availability principle requiring licenses that permit cross-ontology composition), research data (the FAIR principles formalizing three of the four commitments), software (the OSI Open Source Definition codifying them), research publications (the Budapest/Bethesda/Berlin declarations), open standards (W3C/IETF/ISO practice), and open government data (public-data portals). The transfer here is unusually *literal and historically documented*: open-source licensing discipline ported almost without modification into open-access publishing and open-data practice, and the Creative Commons family was explicitly designed to carry the GPL-style architecture into other media. Across all of these the full apparatus carries without translation — the nominal-versus-substantive-openness diagnostic, the technical/legal/social three-layer localization, the per-resource four-commitment checklist plus pairwise license-compatibility, and the enclosure-risk and combinatorial-reach predictions — because every case is the same governance posture applied to a different knowledge-resource medium.

Beyond knowledge resources the named posture does not extend in a structurally non-trivial way, and the honest reading separates a *different prime family* from a *genuinely portable parent*. The tempting extensions — "open access to a forest," "open access to the airwaves" — are *not* instances of open availability at all; they are commons-management problems governed by their own structural primes (`commons`, `tragedy_of_the_commons`), where the resource is rivalrous and the failure mode is overuse, not gated reuse. Confusing the two would be an (A) miscategorization on the shared word "open," and it should be marked off. What *does* generalize is the (B) case: the substantive structural content of open availability is largely the union of parents already in the catalogue — `transparency` (extended to knowledge resources) for the disclosure component, `mediator_availability_constraint` for the access-architecture component, and the governance prime family for the licensing component — and the one sharp move beyond that union is *explicit-license-as-coordination-mechanism*: a pre-authorization that lets strangers combine resources without per-pair negotiation, dropping coordination cost toward zero and unlocking combinatorial composition. That coordination move, now carried by the parent prime `license_as_coordination`, is the portable core, and it is what a cross-domain lesson should carry — wherever pre-declared permissive terms replace per-use negotiation to enable population-scale recombination. Stripped of jargon, "open availability" itself reduces toward a *normative policy posture* ("make knowledge available under explicit permissive terms") rather than a substrate-independent mechanism, which is exactly why its reach stays inside knowledge-resource governance and the exportable structure is the coordination move it instantiates, not the posture as named. See *Structural Core vs. Domain Accent*.