Public Goods Provision

batch: First Iteration/Batch 14

related_primes: tragedy_of_the_commons externality accountability legitimacy reciprocity equity cost_benefit_analysis constraint feedback price_mechanism threshold collective_efficacy

slug: externality

slug: reciprocity

slug: equity

slug: constraint

slug: threshold

components:
Public-Good Boundary
Provision Responsibility
Contribution Rule
Funding Pool
Access Policy
Maintenance Obligation
Legitimacy and Fairness Review
Free-Rider Response
Provision-Level Target
Accountability and Reporting
Assurance Threshold
Matching or Leverage Rule
Volunteer or In-Kind Contribution Path
Benefit Measurement Model
Reserve or Endowment

mechanisms: Public–Private or Multi-Stakeholder Partnership

essence_one_line: Create funding, contribution, or governance mechanisms for resources whose benefits are shared and hard to exclude.

compression_statement: When a good produces broad shared benefit and beneficiaries can receive that benefit without individually paying or contributing, public-goods provision defines the public-good boundary, assigns provision responsibility, pools resources, sets contribution and access rules, and maintains the good so it is not chronically underproduced.

core_intuition: A public good fails because the private incentive to contribute is weaker than the collective value of the good. The solution is not just asking people to be generous; it is building a legitimate provision system that converts diffuse shared benefit into dependable contribution, stewardship, and accountability.

canonical_formula: shared_benefit + hard_to_exclude_beneficiaries + undercontribution_risk -> provision_responsibility + contribution_rule + funding_pool + access_policy + maintenance_governance -> sustained_public_good

structural_problem: A valuable good, service, infrastructure, knowledge base, standard, safety capacity, or shared benefit is underprovided because people can benefit from it even when they do not contribute to its creation or maintenance.

condition: The good is non-excludable, difficult to exclude, or politically or ethically undesirable to exclude from.

why_it_matters: Beneficiaries cannot be reliably charged one by one, so market-like purchase alone underfunds provision.

condition: Use by one beneficiary does not substantially reduce the immediate benefit to others, or the shared benefit diffuses widely.

why_it_matters: Individual willingness to pay is lower than collective value, especially when benefits are dispersed.

condition: Potential contributors wait for others to pay, maintain, organize, or take responsibility.

why_it_matters: Contribution failure becomes rational for each actor even though the group would be better off if enough actors contributed.

condition: The good has creation costs, fixed costs, maintenance costs, coordination costs, or renewal costs that no single beneficiary wants to bear alone.

why_it_matters: Even high-value goods can fail if the cost is lumpy and benefit is distributed.

condition: Legitimate authority, coordination, or contribution governance can be created without destroying the public value of the good.

why_it_matters: The archetype requires a feasible path from shared value to credible provision, not merely recognition that a good would be nice to have.

symptom: Everyone says the resource is important, but no one funds or maintains it reliably.

interpretation: Collective value is not being converted into provision responsibility.

symptom: A small set of contributors or maintainers carries the burden while many more benefit.

interpretation: The provision system is relying on altruism, goodwill, or hidden labor instead of a durable contribution rule.

symptom: The resource is created once but gradually decays, becomes unsafe, outdated, undocumented, or unreliable.

interpretation: Maintenance was not built into the provision model.

symptom: Beneficiaries resist paying because they can still access the benefit if others pay.

interpretation: Free-riding incentives are undermining contribution.

symptom: Voluntary support spikes during crisis or launch but disappears during normal operation.

interpretation: Funding lacks stable governance and renewal cadence.

symptom: Access restrictions are introduced ad hoc because funding or capacity is inadequate.

interpretation: Underprovision is pushing the system toward rationing or club-good drift.

root_tension: The collective value of the good is larger than the value any one actor can privately capture, so individually rational non-contribution prevents or weakens a collectively valuable resource.

case: A good is excludable and rivalrous, and ordinary purchase covers provision and maintenance.

why_not: The problem is not public-goods provision; it may be pricing, capacity, quality, or access design.

case: The main failure is overuse, depletion, congestion, or pollution of an existing shared resource.

why_not: Commons_governance is usually closer because the structural problem is preserving a shared resource from overuse rather than creating an underprovided shared benefit.

case: The central issue is an actor imposing external harm on others.

why_not: Externality_internalization is closer when the key move is making the actor account for spillover harm or benefit.

case: The resource is scarce and must be allocated among competing users.

why_not: Resource_rationing, priority_based_admission, capacity_reservation, or price_signal_design may be closer than provision.

case: The good is mainly a private club benefit with clear exclusion and a bounded paying membership.

why_not: Membership funding may be a mechanism, but the public-goods archetype applies only if shared-benefit underprovision remains central.

structural_intervention: Convert diffuse shared benefit into a legitimate provision system by defining the public-good boundary, assigning responsibility, pooling contributions, governing access, funding maintenance, and reviewing whether the good is actually provided at a sufficient level.

action: Define the public-good boundary.

purpose: Name the good, beneficiaries, benefit diffusion, exclusion constraints, and why individual purchase or voluntary contribution is insufficient.

action: Establish provision responsibility.

purpose: Assign who convenes, funds, governs, maintains, and reports on the good.

action: Choose a contribution and funding structure.

purpose: Turn diffuse beneficiaries or legitimate funders into a predictable funding pool or contribution base.

action: Set access and use rules.

purpose: Preserve the public value of the good while preventing abuse, overload, capture, or exclusionary drift.

action: Build maintenance into the system.

purpose: Ensure that upkeep, renewal, safety, documentation, support, and stewardship are funded and assigned.

action: Monitor provision level, fairness, and adaptation.

purpose: Check whether the good is sufficient, whether burdens are legitimate, and whether contribution or access rules need recalibration.

rule: Use this archetype only when underprovision is caused by shared benefit and contribution failure.

implication: Do not label every desirable resource as a public good.

rule: Match contribution design to beneficiary scope and legitimacy of compulsion.

implication: Broad public benefits can justify public funding; narrower beneficiary groups may need dues, assessments, or cooperative contribution.

rule: Separate launch funding from maintenance funding.

implication: A public good that cannot be maintained is not fully provided.

rule: Keep access as open as the public-good logic requires, but not so open that abuse or overload destroys the good.

implication: Access policy should preserve shared benefit rather than drift into either unmanaged commons or exclusionary club logic.

rule: Review whether contribution burdens match benefit, ability, responsibility, or legitimate policy goals.

implication: A provision system can fail politically or ethically even if it is financially sufficient.

rule: Treat free-rider enforcement as a component, not the whole archetype.

implication: Contribution discipline should serve provision and fairness rather than become punitive control.

invariant: The shared benefit remains genuinely shared.

why_it_matters: Provision should not silently convert a public good into a narrow private entitlement.

invariant: Contribution rules remain legitimate enough to sustain support.

why_it_matters: Public goods rely on trust that burdens and benefits are defensible.

invariant: Maintenance is funded and assigned.

why_it_matters: Creation without upkeep produces decay, burnout, and false confidence.

invariant: Provision level is sufficient for the intended public value.

why_it_matters: Token provision can absorb funding while leaving the structural problem unsolved.

invariant: Access rules prevent abuse without undermining the public-good purpose.

why_it_matters: Both unmanaged access and excessive exclusion can destroy shared value.

invariant: Accountability remains visible to contributors and beneficiaries.

why_it_matters: Opaque provision invites capture, waste, distrust, and withdrawal.

outcome: A shared-benefit good is created, maintained, or expanded where voluntary isolated contribution would fail.

indicator: Reliable funding, stewardship, and access replace chronic underprovision.

outcome: Contribution burden is distributed through an explicit and reviewable rule.

indicator: Support no longer depends only on a few altruistic or overburdened actors.

outcome: Free-riding pressure is reduced without destroying legitimate access.

indicator: Non-contribution no longer threatens the good, and enforcement does not become arbitrary exclusion.

outcome: Public value becomes visible enough to justify continued support.

indicator: Reporting, usage, benefit, quality, or avoided-harm evidence sustains confidence.

outcome: Maintenance and renewal are treated as part of provision.

indicator: The good remains usable after launch, crisis, or initial funding cycles.

prose_essence:
Public Goods Provision is the intervention pattern for shared benefits that are valuable to a group but chronically underproduced by isolated voluntary action. The core move is to stop treating the good as someone else's generosity problem and instead design a legitimate provision system: define the good, pool contributions, assign stewardship, maintain access, and keep the system accountable.

This archetype is especially important when the benefit is diffuse. Everyone may value the good in the abstract, but each actor can rationally wait for others to pay, organize, document, maintain, or protect it. The solution is not merely a tax, grant, donation drive, or sponsorship campaign. Those are mechanisms. The archetype is the broader structure that turns shared value into durable provision.

prose_when_to_use:
Use this archetype when a valuable shared benefit is missing, fragile, underfunded, or maintained by a small overloaded group because beneficiaries can receive value without contributing. The good may be public infrastructure, open-source software, shared standards, public health capacity, scientific data, community preparedness, internal organizational tooling, or ecosystem trust infrastructure.

A strong signal is the sentence: “Everyone depends on this, but nobody owns funding or maintenance.” Another strong signal is invisible contributor burnout: maintainers, public servants, volunteers, or a central team keep a shared good alive while many beneficiaries assume the resource will remain available.

Do not use this archetype just because a resource is popular or socially desirable. Use it when the structural failure is underprovision caused by shared benefit, hard exclusion, diffuse beneficiaries, threshold funding, or contribution failure.

prose_structural_problem:
The structural problem is a gap between collective value and individual incentive. The group would benefit if the good existed at a sufficient level, but any one actor's reason to contribute is weakened because others also benefit. This creates chronic underfunding, delayed maintenance, incomplete coverage, or reliance on hidden labor.

The problem often appears in four forms. First, no one funds creation because benefits are too diffuse. Second, a good is launched but not maintained. Third, a few contributors carry a disproportionate burden. Fourth, access or quality becomes unstable because the provision system never had a legitimate contribution base.

prose_intervention_logic:
The intervention begins by defining the public-good boundary. What exactly is being provided? Who benefits? Why is exclusion impractical, undesirable, or inconsistent with the value of the good? This boundary prevents overclaiming: not every useful resource is a public good.

Next, provision responsibility is assigned. Someone must convene, fund, maintain, report, and adapt the good. Responsibility may belong to a government agency, foundation, cooperative, consortium, platform steward, internal team, association, or coalition.

Then the design creates a contribution rule and funding pool. The contribution rule can be public funding, dues, mandatory assessments, sponsorship, in-kind labor, grants, collective procurement, or a hybrid. The funding pool must be usable for both creation and maintenance.

Finally, the system defines access, maintenance, legitimacy review, and reporting. A public good is not fully provided when it merely exists. It must remain available, sufficiently maintained, and trusted by contributors and beneficiaries.

prose_key_components:
### Public-Good Boundary

The public-good boundary identifies the shared benefit and explains why ordinary individual purchase or voluntary isolated contribution will underprovide it. It names the beneficiaries, the benefit diffusion pattern, and the exclusion problem. Without this component, the label “public good” can become a vague appeal for funding.

### Provision Responsibility

Provision responsibility assigns who is accountable for creating, maintaining, governing, and reporting on the good. A public good with no responsible steward usually becomes an unfunded aspiration or an invisible burden on whoever cares most.

### Contribution Rule

The contribution rule defines who contributes, how much, in what form, and on what basis. It may use ability to pay, benefit received, membership, public obligation, reciprocity, or responsibility for need. This component converts diffuse benefit into concrete support.

### Funding Pool

The funding pool aggregates contributions into usable capacity. It can be a public budget, grant fund, dues account, endowment, shared service budget, sponsorship pool, or cooperative account. The key is that the pool is reliable enough to fund provision and maintenance.

### Access Policy

Access policy defines who can use or benefit from the good and under what conditions. Good access policy preserves shared value while preventing abuse, overload, unsafe use, or capture. Too much exclusion turns the good into a club benefit; too little governance can make the good unsustainable.

### Maintenance Obligation

Maintenance obligation makes upkeep part of the intervention. Public goods often fail because creation is funded but ongoing labor is not. Maintenance includes repair, documentation, safety, moderation, renewal, support, and adaptation.

### Legitimacy and Fairness Review

Legitimacy and fairness review checks whether contribution burdens, access rules, and governance authority can be defended to affected people. This matters because public-goods provision often coordinates or compels contribution. A financially sufficient system can still fail if it feels arbitrary, regressive, or captured.

### Free-Rider Response

Free-rider response handles non-contribution when it threatens provision or fairness. The response may be reciprocity, contribution tracking, recognition, dues, assessments, sanctions, or limited exclusion. It should be proportional and should distinguish strategic non-contribution from inability to contribute.

### Provision-Level Target

The provision-level target defines what counts as enough. A token good that exists but lacks quality, coverage, reliability, or capacity may still be underprovided. This component prevents symbolic provision from being mistaken for real provision.

### Accountability and Reporting

Accountability and reporting show how resources are used and whether the good is producing public value. Reporting keeps contributors engaged, reveals maintenance gaps, and makes recalibration possible.

prose_common_mechanisms:
### Public Funding or Taxation

Public funding or taxation is a mechanism for broad civic goods where benefits are widespread and exclusion is inappropriate. It implements the archetype by creating a legitimate funding pool, but it is not the archetype itself. Without boundary definition, access policy, maintenance duties, and reporting, taxation can fund the wrong thing or fund it badly.

### Mandatory Contribution Schemes

Mandatory contribution schemes require members, beneficiaries, regulated parties, or obligated actors to contribute. They are useful when voluntary contribution repeatedly fails. They require strong legitimacy review because compulsion can become unfair or politically brittle.

### Membership Dues or Assessments

Dues and assessments can sustain shared goods for bounded groups such as associations, neighborhoods, consortia, or cooperatives. They implement contribution governance but can drift toward club-good exclusion if access rules become too narrow.

### Open-Source Sponsorship

Open-source sponsorship supports shared digital infrastructure used by many downstream beneficiaries. It is an implementation of public-goods provision when it funds maintenance, security, documentation, governance, and maintainer capacity rather than functioning as a one-time donation.

### Collective Procurement

Collective procurement pools demand to buy or sustain a shared service. It is useful when individual actors cannot justify full cost but the group can. It must still clarify who benefits, who pays, who governs, and who maintains.

### Grants and Subsidies

Grants and subsidies support goods that private incentives would underprovide. They are often appropriate for research, public-interest infrastructure, environmental goods, and open resources. Their failure mode is dependency on short-term funding or capture by grant-seeking narratives.

### Matching Funds

Matching funds use one contribution to unlock another. They can overcome hesitation and make participation feel more effective. They should not allow major funders to dominate provision priorities without review.

### Assurance Contracts and Pledge Drives

Assurance contracts and pledge drives solve a threshold problem: people contribute only if enough others also commit. They are useful for launching public goods but must be paired with a maintenance model.

### Cooperative Ownership and Multi-Stakeholder Partnerships

Cooperative ownership and multi-stakeholder partnerships combine governance and funding across beneficiaries. They are useful when no single actor has enough legitimacy, resources, or authority. Their risk is governance complexity and capture by the most powerful participants.

### Maintenance Endowments, Reserves, and Volunteer Rotas

Maintenance endowments, reserves, and volunteer rotas sustain the good after launch. They implement the maintenance obligation, but they must not hide unpaid labor burdens or replace durable funding with goodwill alone.

prose_failure_modes:
The most common failure mode is token provision: the good exists nominally but is funded below useful levels. A second is maintenance collapse, where launch funding ends and upkeep falls to invisible labor.

Contributor burnout appears when a small group supports a resource used by many. Club-good drift appears when funders restrict access so aggressively that the public value disappears. Capture appears when administrators or sponsors redirect the good toward their own interests. Free-rider backlash appears when contributors withdraw because non-contribution seems rewarded.

Another failure mode is benefit inflation. Advocates may overstate the public-good character of a resource to secure funding. This is why boundary definition, benefit measurement, and periodic review matter.

prose_neighbor_distinctions:
Public Goods Provision is distinct from Commons Governance. Commons Governance protects an existing shared resource from overuse, depletion, pollution, or neglect. Public Goods Provision creates or sustains an underprovided shared benefit.

It is distinct from Externality Internalization. Externality Internalization changes the decision boundary of an actor who creates spillover costs or benefits. Public Goods Provision builds a collective provision system when beneficial resources are not produced enough because benefits are diffuse.

It is distinct from Free-Rider Mitigation. Free-rider mitigation is a subtype or component focused on non-contribution. Public-goods provision includes the full system of boundary, responsibility, funding, access, maintenance, and accountability.

It is distinct from Resource Rationing. Rationing allocates scarcity. Provision tries to create or sustain enough of the shared good so rationing is less necessary.

It is distinct from Price Signal Design. Taxes, fees, dues, or subsidies may implement provision, but the archetype is not merely a price signal.

prose_cross_domain_examples:
In public health, disease surveillance is a public good because everyone benefits from early warning and reduced spread, even if no single household buys surveillance. Provision requires public funding, accountable agencies, maintenance, and readiness before crisis.

In open-source software, a widely used library may be a public good for an ecosystem. Sponsorship, foundation governance, security audits, maintainer funding, and transparent roadmaps convert diffuse dependency into provision.

In organizations, shared documentation or internal platforms can be public goods. Every team benefits, but no team wants to fund all maintenance. A cross-team budget and accountable owner create provision.

In science, open datasets and reproducibility infrastructure generate benefits across many researchers. Grants, data stewardship, preservation funding, and access rules help maintain the shared resource.

In communities, emergency preparedness equipment and training benefit residents even when use is rare. Assessments, volunteer rotas, reserves, and review keep the good available.

prose_non_examples:
A private subscription product is not Public Goods Provision when access can be withheld and subscribers fund maintenance through ordinary purchase.

A shared pasture being overgrazed is better treated as Commons Governance, because the main problem is overuse of an existing common-pool resource.

Pollution compensation is better treated as Externality Internalization, because the main problem is assigning spillover cost to the actor creating harm.

A scarce medical appointment allocation problem is better treated as rationing, priority admission, or capacity design, because the immediate problem is allocation of limited capacity.

A donor-funded private perk for a narrow group is not a public good unless the shared-benefit boundary and access logic can be defended.

prose_tradeoffs:
Public-goods provision must balance broad access against contribution discipline. The more open a good is, the more free-riding pressure it may face. The stronger the contribution enforcement, the more legitimacy and fairness review it needs.

It must also balance stable provision against capture. A large funder, central agency, or dominant consortium member can make provision possible while also steering the good toward narrow interests.

Measurement creates another tradeoff. Reporting public value helps sustain support, but narrow metrics can undervalue delayed, intangible, or distributed benefits.

Finally, provision creates opportunity cost. A good may be genuinely public and still not be the highest-value use of scarce resources.

prose_invariants_to_preserve:
The shared benefit must remain genuinely shared. If the design quietly converts the good into a private entitlement, it has drifted away from the archetype.

The contribution rule must remain legitimate. Contributors need a defensible reason to believe the burden is fair enough, even if not everyone benefits equally.

Maintenance must be part of the provision promise. A public good that decays after launch is not fully provided.

Access rules must protect both availability and sustainability. Open access without abuse control can destroy the good; excessive access control can privatize it.

Accountability must remain visible. Public-goods provision asks people to trust a collective system; opaque governance erodes that trust.

prose_target_outcomes:
A successful Public Goods Provision design creates or sustains a shared-benefit resource that would otherwise be underprovided. It distributes contribution through an explicit and reviewable rule. It reduces free-riding pressure without undermining legitimate access. It makes public value visible enough to justify continued support. It also funds maintenance, not only creation.

The outcome is not simply more money. The outcome is a durable relation between beneficiaries, contributors, stewards, access, and maintenance.

prose_parameter_dimensions:
The first tuning dimension is beneficiary breadth. A wider beneficiary group may justify public funding, while a narrower group may justify dues, assessments, or cooperative provision. Define the beneficiary group too narrowly and important public value disappears; define it too broadly and contribution responsibility becomes diffuse.

The second dimension is excludability tolerance. Some access control may be needed to prevent abuse or overload, but excessive exclusion can destroy the public-good character.

The third dimension is contribution strength. Voluntary contribution preserves autonomy but may be too weak. Mandatory contribution solves underfunding but requires stronger fairness and legitimacy.

The fourth dimension is provision level. The question is not whether the good exists, but whether it exists at a level that actually delivers the intended shared value.

The fifth dimension is maintenance horizon. Some goods need short-term launch funding; others need durable reserves, endowments, or permanent stewardship.

The sixth dimension is governance centralization. Centralized provision can create reliability and standards, while distributed provision can preserve local fit and participation. Either can fail if pushed too far.

prose_variants_and_near_names:
Important variants include tax-financed provision, assurance-based provision, open-ecosystem provision, member-funded shared-benefit provision, and free-rider mitigation. Free-rider mitigation is recorded as merge-review material because it may be rediscovered as a candidate but usually functions as a subtype inside this archetype.

Near names include collective provision, public goods funding, shared benefit provision, collective funding, and common-good provision. These names are useful for retrieval but need boundary care. “Common-good provision” can easily blur into Commons Governance, while “collective funding” is only a mechanism unless the public-good structure is present.

Mechanism names such as tax, subsidy, grant, dues, crowdfunding, philanthropy, and collective procurement should not be promoted as standalone archetypes here. They are ways to implement provision.

Free-Rider Mitigation

variant_type: subtype

short_definition: Reduce the ability or incentive to benefit from a shared good without contributing when non-contribution threatens provision or fairness.

distinctive_feature: It foregrounds contribution discipline rather than the full design of provision responsibility, funding pool, access, and maintenance.

distinct_from_parent: The parent creates the provision system for a public good; this variant focuses on the specific failure in which beneficiaries avoid contribution.

still_same_parent_because: Free-rider response is usually a component of public-goods provision rather than a standalone intervention family.

use_when: The public good is already defined, but contribution incentives are weakening.

use_when: Non-contributors can benefit while contributors bear the cost.

use_when: Provision, maintenance, or perceived fairness will collapse unless contribution expectations are strengthened.

Contribution Rule

role: Defines expected contribution.

Free-Rider Response

role: Handles non-contribution without undermining access legitimacy.

Legitimacy and Fairness Review

role: Prevents excessive punishment or exclusion.

Mandatory Contribution Scheme

role: Makes contribution enforceable when voluntary support fails.

Membership Dues or Assessments

role: Creates recurring support obligations.

Public Recognition or Reciprocity Norm

role: Uses social reciprocity before stronger enforcement.

example_domains:
open-source maintenance
neighborhood associations
professional standards bodies
public infrastructure

domain: open-source software

example: A widely used project asks commercial dependents to fund maintainers.

domain: community infrastructure

example: A neighborhood association requires assessments to maintain shared lighting.

failure_mode: Punitive exclusion

cause: Contribution enforcement ignores inability to pay or legitimate non-use.

failure_mode: Contribution theater

cause: Visible but low-value contributions substitute for real funding or maintenance.

Tax-Financed Public Goods Provision

short_definition: Use public revenue and public authority to provide a broadly shared good whose beneficiaries cannot be practically charged one by one.

distinctive_feature: It relies on public finance and public accountability rather than voluntary contribution.

distinct_from_parent: The parent can use many funding mechanisms; this variant is the public-budget form.

still_same_parent_because: The same provision logic still applies: define the good, pool resources, provide access, maintain, and account.

use_when: The beneficiary population is broad or diffuse.

use_when: Exclusion would be costly, unjust, or incompatible with the good.

use_when: Public authority has legitimate power to collect and allocate revenue.

Public-Good Boundary

role: Justifies broad public financing.

Funding Pool

role: Aggregates revenue into usable budget.

Accountability and Reporting

role: Supports public oversight.

Public Funding or Taxation

role: Collects and allocates revenue.

Public Budget Appropriation

role: Authorizes funding level.

example_domains:
roads
public health surveillance
basic research
parks
emergency preparedness

domain: public health

example: A public health department funds disease monitoring that benefits everyone.

domain: science

example: Government grants fund basic research whose findings spread widely.

failure_mode: Political underfunding

cause: Benefits are diffuse while budget costs are visible.

failure_mode: Capture by visible beneficiaries

cause: Organized groups redirect the public-good budget toward narrower interests.

Assurance-Based Public Goods Provision

short_definition: Condition contribution on enough others also contributing so people are not left paying for an undelivered or underfunded good.

distinctive_feature: It solves the threshold and assurance problem inside public-goods funding.

distinct_from_parent: The parent includes all provision mechanisms; this variant uses conditional commitment to overcome contribution hesitation.

still_same_parent_because: The goal remains provision of a shared benefit that voluntary isolated contribution would underprovide.

use_when: Potential contributors support the good but doubt others will contribute.

use_when: Provision requires a minimum threshold of money, labor, users, or political support.

use_when: Refund, pledge, or conditional commitment rules can be enforced.

Assurance Threshold

role: Sets the required contribution level.

Contribution Rule

role: Defines pledge or refund conditions.

Assurance Contract

role: Activates contributions only when the threshold is met.

Crowdfunding or Pledge Drive

role: Coordinates many conditional commitments.

example_domains:
community projects
software maintenance funding
civic infrastructure
research tools

domain: community

example: Residents pledge funds for a shared amenity only if the full target is reached.

example: Sponsors commit to fund a maintainer if enough dependent firms join.

failure_mode: Threshold miss despite real value

cause: The target, timeline, or communication fails to coordinate contributors.

failure_mode: Launch without maintenance

cause: The assurance threshold covers creation but not ongoing stewardship.

Open-Ecosystem Public Goods Provision

short_definition: Fund and steward open resources such as software, standards, documentation, datasets, or protocols that many actors depend on without exclusive ownership.

distinctive_feature: It foregrounds open participation, ecosystem dependency, and maintainer sustainability.

distinct_from_parent: The parent is domain-general; this variant addresses open infrastructure and knowledge ecosystems.

still_same_parent_because: The structural problem is still underprovided shared benefit due to diffuse beneficiaries and free-riding.

use_when: The shared good is open, reusable, or ecosystem-wide.

use_when: Many beneficiaries depend on it but no single beneficiary owns the maintenance duty.

use_when: Sponsorship, maintainer funding, governance, and contribution norms can stabilize provision.

Maintenance Obligation

role: Protects ongoing upkeep of open resources.

Volunteer or In-Kind Contribution Path

role: Supports non-monetary contribution.

Accountability and Reporting

role: Shows sponsors and users what support enables.

Open-Source Sponsorship

role: Funds maintainers and shared tooling.

Grant or Subsidy Program

role: Supports ecosystem resources with public or philanthropic funds.

Volunteer Contribution Rota

role: Distributes stewardship labor.

example_domains:
open-source software
open data
standards bodies
scientific infrastructure

example: Dependent companies fund maintenance of a core library.

example: A shared dataset receives ongoing support for curation and access.

failure_mode: Maintainer burnout

cause: Use grows faster than contribution and governance capacity.

failure_mode: Sponsor capture

cause: A large funder steers priorities away from the wider ecosystem.

Member-Funded Shared Benefit Provision

short_definition: Use dues, assessments, or cooperative governance to provide a good shared by an identifiable beneficiary group.

distinctive_feature: It uses bounded membership to make contribution feasible while still supporting a shared benefit.

distinct_from_parent: The parent may be fully public or open; this variant is organized around an identifiable contributing group.

still_same_parent_because: The good remains collectively provided and underprovided without contribution coordination.

use_when: The beneficiary group is bounded enough to organize contributions.

use_when: Universal public funding is unavailable or inappropriate.

use_when: The access policy must avoid drifting into narrow club exclusion unless that is intentional.

Access Policy

role: Defines membership and access boundaries.

Contribution Rule

role: Defines dues or assessment obligations.

Legitimacy and Fairness Review

role: Checks whether member burdens and access are defensible.

Membership Dues or Assessments

role: Funds the shared resource.

Cooperative Ownership

role: Aligns provision governance with beneficiaries.

example_domains:
professional associations
cooperatives
neighborhood associations
research consortia

domain: professional standards

example: Members fund a standards body that benefits the field.

example: Residents fund shared emergency equipment through assessments.

failure_mode: Club-good drift

cause: Contribution enforcement turns a public-benefit good into exclusionary access.

failure_mode: Member capture

cause: Large contributors dominate governance.

near_names:
Collective Provision
Public Goods Funding
Shared Benefit Provision
Collective Funding
Common-Good Provision
Free-Rider Solution


Pulse Release

type: archetype

source: generated

batch: First Iteration/Batch 21/Wave 2

Pulsed Release

notes: Grammatical variant of Pulse Release.

Pulse Dosing

notes: Often an implementation mechanism or domain analogy; it should not be treated as the full archetype unless release size, interval, response, and recovery logic are explicit.

Drip Release

notes: A gradual sequence of small pulses, often used in communication or fundraising contexts.

Batch Release

notes: A release mechanism that can instantiate Pulse Release when batching is deliberately used to match absorption or recovery windows.

Tranche Release

notes: A funding, resource, or governance implementation where resources are released in planned pulses.

Campaign Pulsing

notes: A communication or attention-management implementation of pulsed release.

related_primes: intermittency absorptive_capacity feedback threshold resource_management adaptation damping amplification state_and_state_transition coupling homeostasis optimization resilience scheduling

slug: periodicity

slug: resonance

slug: intermittency

slug: feedback

slug: adaptation

slug: damping

slug: amplification

slug: coupling

slug: homeostasis

slug: optimization

slug: resilience

slug: scheduling

components:
Pulse Payload
Pulse Size
Pulse Interval
Response Window
Recovery Interval
Absorption Capacity Signal
Cessation or Escalation Rule
Anti-Stacking Guardrail
Receiver Segment
Pulse Sequence Plan
Quiet Period
Baseline Support Channel

mechanisms:
Drip Campaign
Pulse Dose
Batch Release
Staged Announcement
Training Interval Sequence
Resource Tranche
Campaign Burst
Adaptive Release Gate

essence_one_line: Release resources, information, or effort in deliberate pulses rather than a continuous stream so the receiving system can notice, absorb, respond, and recover.

compression_statement: When continuous input is wasted, ignored, or overwhelming because a system absorbs, notices, or responds episodically, define pulse size, interval, response window, recovery window, and stop/escalation rules so each release has enough force to matter without stacking into overload.

core_intuition: A stream is not always easier to handle than a burst. Some systems need quiet intervals to integrate what arrived, regain attention, replenish capacity, or show a response signal. Pulse Release uses bounded packets and intentional spacing to make input legible, actionable, and recoverable.

canonical_formula: continuous_input + pulse_size + pulse_interval + response_window + recovery_window + feedback_rule -> absorbable_release_sequence

structural_problem: A sender, producer, funder, trainer, coordinator, or support system emits input continuously or too diffusely, while the receiving system can only attend to, absorb, process, or respond in bounded episodes.

description: Ongoing exposure produces diminishing response, habituation, confusion, waste, or background noise rather than useful action.

description: The receiving system has identifiable periods of attention, capacity, readiness, recovery, consolidation, or decision-making.

description: Useful response cannot be forced by simply increasing volume; time between releases changes uptake quality.

description: The input can be packaged into discrete pulses without unacceptable safety, equity, or continuity harms.

description: The designer can observe enough response, fatigue, backlog, or recovery evidence to retune pulse size or timing.

description: Frequent communication becomes ambient noise, so important signals are ignored.

description: The receiver cannot process everything being sent and begins to drop, defer, or distort inputs.

description: Each additional unit of input produces less response because attention or capacity has not recovered.

description: The sender cannot tell what worked because new input arrives before the previous input has had a measurable response window.

description: A persistent stream creates fatigue, resistance, gaming, or disengagement.

root_tension: The input source is optimized for steady pushing or constant availability, while the receiver is optimized for episodic attention, bounded absorption, recovery, and response measurement.

why_not_this_archetype: Some functions require continuous service, safety monitoring, life support, or real-time control; pulsing those inputs may be unsafe.

why_not_this_archetype: A release is not Pulse Release merely because items are batched; the pulse must be intentionally sized and spaced around receiver absorption or response.

why_not_this_archetype: If the core problem is smoothing load or avoiding synchronized peaks, Load Leveling, Demand Smoothing, or Cycle Staggering may be the better archetype.

why_not_this_archetype: If the central logic is amplification by matching a system-specific response frequency, Resonance Tuning is the stronger parent.

why_not_this_archetype: A single announcement, grant, launch, or intervention is not a pulse sequence unless it is part of a recurring release design.

structural_intervention: Replace an undifferentiated stream with an explicitly governed sequence of discrete releases, each with a defined payload, size, interval, response window, recovery window, monitoring signal, and rule for stopping, spacing, or escalating.

logic: Define the receiving system and what counts as successful absorption, response, or recovery.

logic: Convert the continuous or diffuse input into bounded pulse payloads that are large enough to be noticed but small enough to process.

logic: Set an initial interval and recovery window based on receiver capacity, attention decay, operational cycle, or prior response evidence.

logic: Release a pulse, then protect the response window so the receiver can act and the sender can measure uptake before the next pulse arrives.

logic: Use response, fatigue, backlog, error, and recovery signals to retune pulse size, spacing, content, or cessation rules.

logic: Stop, taper, escalate, or change channel when pulse response saturates, fatigue rises, or the objective is reached.

description: Set pulse size by what the receiver can interpret or use, not by how much the sender wants to push.

description: Do not send the next pulse before the previous one has had a fair chance to produce observable response and recovery.

description: If receiver fatigue, backlog, confusion, or overload rises, widen the interval, reduce the pulse, change channel, or stop.

description: Pulse design should change when response falls, recovery lengthens, or the receiver adapts to the rhythm.

description: Do not pulse inputs that must remain continuously available for safety, care, service reliability, or fairness.

description: The sequence must not exceed the receiving system's ability to notice, process, decide, or recover.

description: Participants should be able to tell when a pulse starts, what it asks for, and when the response window ends.

description: Quiet periods are part of the design, not unused time waiting to be filled.

description: Changes to pulse size or interval should be based on response and fatigue evidence, not only impatience.

description: Pulsing must not withdraw necessary baseline support, information, or protection.

description: Each release is more likely to be noticed, understood, used, or acted upon.

description: The receiving system gets recovery intervals that reduce habituation and resistance.

description: Pulse boundaries make it easier to attribute response to a release rather than to an ongoing stream.

description: Size, spacing, and stopping rules become explicit design variables rather than accidental habits.

description: The system avoids both continuous pressure and complete inactivity by using bounded, timed releases.

prose_essence:
Pulse Release is the pattern of turning an ineffective stream into a deliberately paced sequence of releases. The thing being released may be information, work, funding, training load, software change, public guidance, or a demand stimulus. The key is not that the release is simply periodic. The key is that each pulse is sized and spaced so the receiving system can notice it, absorb it, respond to it, and recover before the next pulse arrives.

A continuous stream often seems generous or efficient from the sender's side, but it can be wasteful from the receiver's side. People tune out constant messages, teams cannot absorb continuous change, support systems cannot evaluate adoption when another wave arrives immediately, and resource recipients may be overwhelmed by more input than they can put to use. Pulse Release treats quiet intervals as part of the intervention.

prose_when_to_use:
Use Pulse Release when continuous input is ignored, diluted, overwhelming, or hard to measure. The pattern is especially useful when the receiver has bounded attention, processing capacity, emotional energy, operational capacity, or readiness windows. It is also useful when the sender needs to learn from response before sending more.

The archetype fits best when the payload can be divided into coherent units, when response can be observed, and when the interval between releases changes outcomes. A training sequence, staged rollout, grant tranche, campaign burst, or bounded communication wave can all instantiate the pattern if they include pulse size, pulse interval, response window, recovery interval, and feedback rules.

Do not use Pulse Release for inputs that must be continuous for safety, care, reliability, legal access, or real-time control. Do not call something Pulse Release merely because it is batched. Sender convenience is not enough; receiver absorption must be the design logic.

prose_structural_problem:
The structural problem is a mismatch between sender flow and receiver absorption. One side can produce, push, fund, announce, train, or stimulate continuously. The other side can only process, act, recover, or respond in episodes. When those two structures are misaligned, more input can produce less uptake.

Symptoms include message blindness, backlog, response decay, attention fatigue, repeated clarification requests, adoption stalls, and confusing outcome data. The sender may think the problem is insufficient volume, while the receiver is actually saturated. Adding more pressure makes the system noisier rather than more effective.

prose_intervention_logic:
Pulse Release intervenes by making release boundaries explicit. First, define the receiving system and what successful absorption looks like. Then package the input into a coherent pulse payload. Set the pulse size so it crosses the threshold for notice or action without exceeding processing capacity. Set a pulse interval and response window. Protect recovery time. Monitor response and fatigue signals. Then decide whether to stop, widen the interval, reduce the pulse, intensify it, or redirect it.

The intervention works because it turns release timing into a design variable. Instead of asking, “How much can we send?” it asks, “What amount can be absorbed now, what response should we expect, and when will the receiver be ready for the next pulse?”

prose_key_components:
### Pulse Payload

The pulse payload is what gets released: a message, task, grant, supply, feature, prompt, training load, or stimulus. A payload should be coherent enough to be understood as one unit. If the payload is arbitrary, the pattern becomes batching rather than Pulse Release.

### Pulse Size

Pulse size sets the amount, scope, intensity, or volume of each release. Too small a pulse may not be noticed or acted on. Too large a pulse may overload the receiver and collapse into dumping. Pulse size should be calibrated against absorption capacity, not only sender backlog.

### Pulse Interval

The pulse interval is the gap or condition separating one release from the next. It may be fixed, adaptive, event-triggered, or recovery-gated. The interval matters because it gives the receiver time to respond and gives the sender time to learn.

### Response Window

The response window is the period in which the receiver is expected to notice, act, integrate, or produce evidence after a pulse. Without a response window, the sender may misread slow uptake as failure and send more too soon.

### Recovery Interval

The recovery interval is protected time for attention, capacity, emotion, or operations to reset. It prevents dose stacking and makes the next pulse legible. In many cases, the quiet period is as important as the release itself.

### Absorption Capacity Signal

An absorption capacity signal tells the designer whether the receiver has processed the release. It might be completion rate, backlog, error rate, sentiment, adoption, retention, fatigue, support tickets, or requests for help.

### Cessation or Escalation Rule

The cessation or escalation rule defines when to stop, taper, widen, intensify, redirect, or escalate the sequence. Without this rule, pulse sequences can become endless campaigns that exhaust the receiver.

### Anti-Stacking Guardrail

An anti-stacking guardrail prevents pulses from accumulating faster than the receiver can absorb them. It may be a maximum frequency, blackout window, backlog threshold, fatigue cutoff, or readiness gate.

prose_common_mechanisms:
Drip campaigns, pulse doses, batch releases, staged announcements, training interval sequences, resource tranches, campaign bursts, and adaptive release gates can all implement Pulse Release. These mechanisms are not the archetype by themselves. They become Pulse Release only when they are governed by payload size, interval, response window, recovery interval, and feedback.

A **drip campaign** implements attention pulsing by sending a sequence of small messages rather than a constant stream. A **batch release** packages updates or resources into discrete units, but it should collapse into Load Leveling if the purpose is only operational smoothing. A **resource tranche** releases funding or supplies in stages tied to readiness and uptake. An **adaptive release gate** allows the next pulse only when the receiver appears ready.

prose_failure_modes: The most common failure mode is **dose stacking**, where the next pulse arrives before the receiver has recovered. **Pulse fatigue** occurs when pulses become spam. **Underdosed release** occurs when pulses are too small to matter. **Response window crowding** occurs when other demands occupy the time meant for uptake. **Misread feedback** occurs when noisy metrics are mistaken for true readiness. **Manipulative intermittency** occurs when pulses exploit attention or urgency rather than supporting absorption. **Unsafe withholding** occurs when essential support is pulsed even though it should be continuous.

prose_neighbor_distinctions:
Pulse Release differs from **Resonance Tuning** because it does not require matching a natural response frequency. It may use timing evidence, but the core pattern is bounded release for absorption and recovery.

It differs from **Cadence Design** because cadence design establishes recurring rhythm, while Pulse Release governs payload size, response windows, recovery intervals, and stopping rules.

It differs from **Load Leveling or Demand Smoothing** because Pulse Release may intentionally create bounded peaks. Load leveling smooths demand; Pulse Release packages input so it can be absorbed.

It differs from **Recovery Interval Design** because recovery is one component, not the whole pattern. It differs from **Intermittent Burst Absorption** because Pulse Release creates outgoing pulses, while burst absorption prepares for irregular incoming spikes.

prose_cross_domain_examples: In organizational communication, a rollout team may send one action-oriented instruction at a time, wait for feedback, and then release the next instruction. In training, a coach may release practice challenges in pulses separated by consolidation intervals. In grantmaking, funds may be released in tranches when recipients show readiness and absorption. In software, features may be released to cohorts with support monitoring before the next wave. In public information, short action bursts may be separated by quiet intervals to reduce message fatigue.

prose_non_examples: A daily reminder with no response check is not Pulse Release. A one-time product launch is not a pulse sequence. A bulk release caused by sender backlog is not Pulse Release unless receiver absorption drives the design. A continuous safety alert stream is not Pulse Release if real-time continuity is required. Staggered shifts are usually Cycle Staggering or Load Leveling rather than Pulse Release.

prose_tradeoffs: Pulse Release trades speed for absorption. It can improve uptake but slow total delivery. It can make signals more salient but also create fatigue if overused. It can improve measurement but requires monitoring. In resource settings, staged release can protect absorption but may also create unfair delay if criteria are opaque. In operational settings, pulses may create peaks that require load leveling or staggering.

prose_invariants_to_preserve: Pulse Release should preserve receiver absorption capacity, legible release boundaries, protected recovery time, feedback before retuning, and essential baseline continuity. The design fails if every interval becomes filled with new demands, if pulses arrive before response can be observed, or if important continuous support is withdrawn in the name of pacing.

prose_target_outcomes: The target outcomes are higher absorption per unit input, lower fatigue, clearer response measurement, better release governance, and reduced overload without complete withholding. When the archetype works, the receiving system has a better chance to use what arrives, and the sender has a clearer basis for deciding what to send next.

prose_parameter_dimensions:
The main tuning dimensions are pulse size, interval length, response window duration, recovery interval duration, receiver segmentation, payload coherence, feedback threshold, and stop/escalation rule. Each dimension can be adjusted independently.

A large pulse with a long interval can create focus and strong response, but it may also create peaks. Small pulses with short intervals can maintain momentum, but they may become noise. Recovery-gated pulses adapt to receiver state, but they require reliable readiness signals. Fixed pulses are easier to govern but can become stale or misaligned.

prose_variants_and_near_names:
Recognized variants include attention pulsing, recovery-gated pulse release, resource tranche release, and learning interval release. Near names include pulsed release, pulse dosing, drip release, tranche release, campaign pulsing, and batch release.

Batch Release, Pulse Dose, Drip Campaign, Calendar Reminder, and Metronome should not be promoted as standalone archetypes here. They are mechanisms, aliases, or neighboring patterns unless their future evidence shows distinct cross-domain intervention logic.

raw_bundle_path: solution_archetypes/_Batches/First Iteration/Batch 21/Wave 2/pulse_release_solution_archetype_output_bundle.zip

Attention Pulsing

short_definition: Release communication or prompts in bounded bursts so recipients notice and act before attention decays.

distinctive_feature: The limiting factor is recipient attention rather than physical capacity or resource uptake.

distinct_from_parent: The parent can release any kind of input; this variant specifically handles attention and communication payloads.

still_same_parent_because: It still uses pulse size, interval, response window, recovery, and feedback to govern release.

condition: Continuous messages have become ambient noise.

condition: Recipients need a clear action window and quiet periods between prompts.

Pulse Payload

role: Defines the message or prompt.

Response Window

role: Defines expected recipient action time.

Quiet Period

role: Prevents message fatigue.

Drip Campaign

role: Sequences short messages.

Staged Announcement

role: Releases information in ordered waves.

domain: Public communication

example: Short action reminders released around specific deadlines rather than constant reminders.

domain: Organizational change

example: A rollout sends one behavior change at a time, then pauses for adoption feedback.

description: Too many pulses become spam.

description: Pulses exploit urgency or scarcity rather than supporting comprehension.

Recovery-Gated Pulse Release

short_definition: Allow the next pulse only after recovery, backlog, or readiness signals show that the receiver can absorb it.

distinctive_feature: The interval is conditional on recovery evidence instead of purely scheduled timing.

distinct_from_parent: The parent may use fixed or adaptive intervals; this variant makes recovery gating central.

still_same_parent_because: It remains a pulse sequence, not a standalone recovery archetype.

condition: Fixed intervals risk dose stacking.

condition: Receiver readiness varies with workload, fatigue, or recovery state.

Recovery Interval

role: Protects reset time.

Absorption Capacity Signal

role: Confirms readiness.

Adaptive Release Gate

role: Permits or blocks next pulse.

role: Controls next release.

Resource Tranche

role: Releases resources after readiness evidence.

example_domains: software_rollout grantmaking training operations

domain: Software

example: A rollout waits for support tickets and error rates to recover before the next feature wave.

domain: Training

example: The next workload pulse begins only after recovery and performance checks pass.

description: Gates become so conservative that useful release stalls.

description: A misleading signal greenlights the next pulse too early.

Resource Tranche Release

short_definition: Release money, supplies, permissions, staff support, or capacity in discrete tranches tied to uptake, milestones, or absorption evidence.

distinctive_feature: The payload is a resource allocation rather than communication, work, or training load.

distinct_from_parent: The parent is domain-general; this variant concerns resource governance and allocation risk.

still_same_parent_because: It still governs pulse size, interval, response evidence, and next-release rules.

condition: Full upfront release would overwhelm, waste, or reduce accountability.

condition: Recipients can absorb resources better in staged waves.

Pulse Size

role: Sets tranche magnitude.

Cessation or Escalation Rule

role: Controls next tranche.

Resource Tranche

role: Implements staged resource release.

domain: Grantmaking

example: Funds are released in staged tranches after recipients demonstrate use and readiness.

domain: Supply

example: Supplies are released in waves to match distribution and storage capacity.

description: Tranching denies needed resources despite evident need.

description: Review gates slow useful uptake.

Learning Interval Release

short_definition: Release practice, instruction, or challenge load in pulses separated by consolidation and feedback windows.

distinctive_feature: The receiver is a learning process with consolidation and transfer constraints.

distinct_from_parent: The parent includes any payload; this variant focuses on instruction, practice, and skill acquisition.

still_same_parent_because: The causal structure remains pulse payload, interval, response, recovery, and retuning.

condition: Continuous instruction overwhelms retention or practice quality.

condition: Learners need time to consolidate before receiving more input.

Response Window

role: Allows practice and feedback.

Recovery Interval

role: Allows consolidation.

Training Interval Sequence

role: Alternates load and consolidation.

example_domains: education training coaching organizational_change

domain: Workplace learning

example: A team receives one workflow practice challenge per week rather than all procedures at once.

failure_mode: underchallenge

description: Pulses are too small to sustain learning momentum.

description: Pulses arrive before consolidation is complete.

near_names:
Pulsed Release
Pulse Dose
Drip Campaign
Batch Release
Tranche Release
Campaign Burst


Purity-Pollution Boundary Governance

batch: Batch 03

canonical_family: Contamination & Purification

aliases:
Purity and Pollution Governance
Contamination Boundary Governance
Clean/Unclean Status Management
Taint and Cleansing Design
Ritual Purity Governance
Contamination-and-Cleansing Pattern
Symbolic Contamination Management
Purification Path Design

source_primes: purity_and_pollution contagion symbolic_boundaries ritual classification containment sacred

related_primes: cascade determinism taboo boundary normativity social_norms legitimacy set_and_membership diffusion sequestration liminality moral_panic markedness reification access_control psychological_safety equity

slug: contagion

slug: ritual

slug: classification

slug: containment

slug: sacred

slug: cascade

slug: determinism

slug: taboo

slug: boundary

slug: normativity

slug: legitimacy

slug: diffusion

slug: sequestration

slug: liminality

slug: markedness

slug: reification

components:
Purity Category Frame
Contaminant or Taint Signature
Contact-Transfer Model
Boundary Marker System
Containment or Separation Rule
Cleansing or Restoration Path
Authority and Legitimacy Basis
Proportionality and Scope Limit
Reentry or Reacceptance Rule
Status Trace and Audit Record
Dignity and Non-Scapegoating Guardrail
Cross-Context Translation Note
Quarantine or Holding Zone
Chain-of-Custody Linkage
Contamination Threshold Rule
Exception or Appeal Path
Ceremonial Reintegration Frame

mechanisms:
Validated Clean-Down Protocol
Quarantine Label and Hold
Red/Green Status Tagging
Allergen Segregation Plan
Aseptic Field Protocol
Ritual Ablution or Cleansing Act
Tainted Data Quarantine
Chain-of-Custody Log
Symbolic Reintegration Ritual
Stigma Escalation Review
Pollution Pricing or Liability Rule

essence_one_line: Make clean/contaminating status, transfer paths, containment rules, and restoration paths explicit so purity logic can protect without becoming arbitrary exclusion.

compression_statement: Purity-Pollution Boundary Governance applies when a system treats some contact, material, action, symbol, association, or status as capable of contaminating another entity. The archetype converts tacit clean/unclean judgment into an explicit governance pattern: define purity categories, identify the contaminant or taint signature, map contact and transfer paths, mark boundaries, contain spread, provide cleansing or restoration steps, and audit authority and proportionality. It covers material contamination and symbolic/ritual pollution while requiring strong safeguards against scapegoating, caste-like permanence, and metaphor drift from hygiene into moral exclusion.

core_intuition: Purity rules are powerful because they compress complex risk, meaning, and belonging into simple status marks. They become dangerous when the status mark is invisible, irreversible, or detached from a legitimate transfer model. Governance makes the mark visible, bounded, contestable, and restorable.

canonical_formula: managed purity status = category frame P + transfer model T + boundary markers B + containment rule C + restoration path R + legitimacy/proportionality guard G

structural_problem: A community, organization, process, or technical system must distinguish what can safely or legitimately mix from what must be separated, cleansed, quarantined, or restored. If purity and pollution logic remains tacit, it can either fail to protect against real transfer or overreact by marking people, objects, spaces, or records as permanently contaminating.

trigger_conditions: Contact, association, proximity, lineage, reuse, data provenance, or symbolic participation can change status.

trigger_conditions: The system needs to distinguish clean, contaminated, uncertain, restricted, sacred/protected, or restored states.

trigger_conditions: Unwanted transfer can cascade across spaces, networks, processes, groups, materials, or records.

trigger_conditions: Cleansing, quarantine, disposal, reclassification, or reintegration must be accepted as legitimate by participants.

trigger_conditions: The same logic might mix material risk with symbolic meaning, moral status, religious practice, or social belonging.

trigger_conditions: Unclear authority over classification or restoration creates dispute, fear, stigma, or unsafe reuse.

symptoms: Participants disagree about whether something is contaminated, clean, restricted, or safe to use.

symptoms: Purity rules are invoked inconsistently, escalating suspicion or moral panic.

symptoms: Objects, spaces, data, or people remain informally marked even after a supposed cleansing step.

symptoms: Containment is either too weak to stop transfer or so broad that it creates unnecessary exclusion.

symptoms: A material hygiene rule is used as a metaphor for social or moral worth without scrutiny.

symptoms: Records show disposal or isolation but not the contact pathway, authority, threshold, or restoration logic behind it.

root_tension: The system must protect boundaries and meaning-bearing statuses, but the same clean/unclean distinction can become self-sealing, contagious, and ethically dangerous when it is not bounded by evidence, legitimacy, proportionality, and restoration.

anti_signatures: The main task is merely to slow a harmful spread through a network; use Diffusion Containment when clean/unclean status and restoration are not central.

anti_signatures: The main task is regulating any crossing of an interface; use Boundary Permeability Control when no purity or contamination classification is involved.

anti_signatures: The main task is redesigning identity or status boundaries; use Symbolic Boundary Reframing when taint, contagion, and cleansing are not central.

anti_signatures: The main task is navigating a forbidden topic or action; use Taboo Boundary Navigation when contact-transfer and restoration rules are secondary.

anti_signatures: The main task is introducing a shared sacred focal object; use Sacred Object or Totem Introduction when purity governance is only contextual.

anti_signatures: The classification permanently dehumanizes a group or treats identity as contamination; this is a misuse case, not a valid application.

structural_intervention: Design an explicit purity/pollution governance system that states what status categories exist, how contamination transfers, how boundaries are marked, how spread is contained, how cleansing or restoration occurs, and how authority, proportionality, dignity, and reentry are checked.

action_logic: Name the domain of concern: material safety, ritual status, data integrity, public health, evidence handling, environmental harm, or social meaning.

action_logic: Define the clean, contaminated, uncertain, restricted, protected, restored, and exception states that will be used.

action_logic: Specify the contaminant or taint signature and distinguish empirical hazard from symbolic, ritual, legal, or reputational status.

action_logic: Map contact, association, lineage, proximity, reuse, or participation pathways by which status is believed to transfer.

action_logic: Choose boundary markers that make status legible without overexposing or humiliating affected people.

action_logic: Create containment, separation, quarantine, or handling rules proportional to the transfer model.

action_logic: Define cleansing, decontamination, expiration, disposal, apology, ritual, certification, or reintegration steps that can restore status when appropriate.

action_logic: Assign accountable authority for classification, exception handling, restoration verification, and dispute review.

action_logic: Audit dignity, equity, and non-scapegoating risks before applying purity logic to people or groups.

action_logic: Record status transitions and review whether the system is preventing real harm without creating unnecessary permanent marks.

decision_rules: Do not impose containment without naming the transfer model it is meant to interrupt.

decision_rules: Separate empirical contamination from symbolic or moral pollution before selecting mechanisms.

decision_rules: Use the least exclusionary boundary that still protects the legitimate purpose.

decision_rules: Make restoration possible by default unless the domain justifies irreversible disposal or exclusion.

decision_rules: When purity status affects people, require dignity, proportionality, appeal, and reentry safeguards.

decision_rules: Do not allow metaphors of cleanliness to replace evidence, consent, procedural fairness, or ethical judgment.

decision_rules: Escalate to human review when purity classifications align with protected identity categories, public shaming, or collective blame.

target_invariants: Purity or contamination status is explicit rather than tacit.

target_invariants: Transfer rules are bounded and inspectable.

target_invariants: Containment follows the stated transfer model.

target_invariants: Restoration, reentry, or disposal criteria are defined before enforcement.

target_invariants: Classification authority is legitimate and accountable.

target_invariants: Human dignity is not reduced to clean/unclean status.

target_invariants: Symbolic meanings are not smuggled in as empirical hazard claims.

expected_outcomes: Cleaner separation between real hazard, symbolic meaning, moral judgment, and social control.

expected_outcomes: Reduced cross-contamination, compromised provenance, or unsafe mixing where transfer risk is real.

expected_outcomes: More legitimate and understandable cleansing or restoration processes.

expected_outcomes: Less arbitrary stigma, scapegoating, moral panic, and permanent marking.

expected_outcomes: Better auditability of containment, restoration, and status transitions.

Material Decontamination Variant

short_definition: Uses clean/contaminated status, contact-transfer rules, and validated clean-down to govern material safety.

distinctive_feature: The contaminant is materially hazardous or process-compromising rather than primarily symbolic.

distinct_from_parent: It narrows the parent to empirical contamination and validated material restoration.

still_same_parent_because: The same category, transfer, boundary, containment, and restoration structure governs the case.

use_when: Food, lab, clinical, industrial, or environmental materials can cross-contaminate.

use_when: Clean status must be restored and verified before reuse.

example: Allergen tools remain marked until clean-down verification restores status.

failure_modes: Assuming visual cleanliness equals restored status.

failure_modes: Applying zero-contact rules when thresholds and validation would suffice.

Ritual Purity Restoration Variant

short_definition: Uses culturally legitimate rites or abstentions to mark transition between impure, liminal, and restored states.

distinctive_feature: Legitimacy depends on ritual authority and shared meaning.

distinct_from_parent: It specializes the parent for symbolic or religious practice.

still_same_parent_because: It still uses purity categories, transfer rules, boundary markers, and restoration paths.

source_primes: purity_and_pollution ritual sacred

use_when: Status depends on shared ritual meanings rather than laboratory hazard.

use_when: Restoration must be publicly or normatively recognized.

example: A prescribed ablution marks a transition back into ordinary participation.

failure_modes: Treating external interpretation as more authoritative than participant meaning.

failure_modes: Using ritual categories outside their legitimate context.

Social Stigma Containment Variant

short_definition: Audits and limits purity logic when it begins marking persons or groups as contaminating.

distinctive_feature: The central work is harm prevention against purity logic itself.

distinct_from_parent: It is a safeguard-focused variant rather than an ordinary containment design.

still_same_parent_because: It acts on the same purity/pollution status system and restores legitimate boundaries.

use_when: Purity language is moving from practices or materials onto identity.

use_when: Restrictions risk scapegoating, humiliation, or permanent exclusion.

example: Messaging treats exposure as a temporary status, not a moral identity.

failure_modes: Containment policy becomes collective blame.

Tainted Information Restoration Variant

short_definition: Marks, quarantines, cleanses, rejects, or downgrades information whose provenance or transformation path compromises trust.

distinctive_feature: The contaminant is compromised provenance or interpretive trust rather than physical substance.

distinct_from_parent: It narrows the parent to information-integrity handling.

still_same_parent_because: The same taint, boundary, quarantine, restoration, and trace logic applies.

use_when: Data, evidence, or claims inherit trust status from source or handling history.

use_when: Downstream use requires explicit restoration or rejection.

example: Records from an untrusted import remain tainted until validation transforms and release criteria pass.

failure_modes: Trust is laundered by format conversion rather than validated restoration.

near_names:
Contamination and Cleansing
Ritual Purity
Taint and Purification
Defilement


Purpose Alignment Design

batch: First Iteration/Batch 42

source_primes: teleology goal_congruence function

related_primes: backcasting visioning optimization feedback normativity accountability transparency observability trade_offs sociotechnical_systems

slug: teleology

slug: function

slug: backcasting

slug: visioning

slug: optimization

slug: feedback

slug: accountability

slug: transparency

slug: observability

components:
Purpose Statement
End-State Definition
Means-Purpose Map
Misalignment Diagnosis
Redesign Lever
Purpose Drift Monitor
Beneficiary Definition
Nonpurpose Boundary
Metric Proxy Check
Purpose Owner

mechanisms:
Purpose-to-Metric Mapping
Mission Alignment Review
Outcome-Driven Design
Function Analysis Workshop
Backcasting from Purpose
Goal Alignment Workshop
Product Purpose Review
Purpose-Clause Decision Record

essence_one_line: Align means, functions, and decisions with the purpose or end state they are supposed to serve.

compression_statement: When activity drifts from its intended purpose, clarify the end state and redesign means, metrics, and decisions so they serve that purpose.

core_intuition: A means is not justified by being familiar, measurable, efficient, or locally useful. It is justified by the end it serves. Purpose Alignment Design makes that means-end relation explicit, tests whether it still holds, and redesigns the system where the relation has broken.

canonical_formula: Purpose P + end-state E + current means M + decisions D + metrics R => align when each consequential M/D/R materially serves P/E, conflicts are made explicit, and drift is monitored over time.

structural_problem: A process, tool, role, or organization continues operating without clear connection to the purpose it was meant to serve.

trigger_conditions: A process, role, product feature, metric, policy, or program continues despite unclear contribution to the stated purpose.

trigger_conditions: People agree on activity but not on what end the activity is supposed to serve.

trigger_conditions: Local optimization improves a proxy measure while the real purpose is stagnant, harmed, or invisible.

trigger_conditions: A legacy function once served a valid purpose but conditions have changed.

trigger_conditions: A decision requires choosing among competing means, and the choice cannot be settled without clarifying the end state.

symptoms: Mission or purpose language appears in documents but does not constrain budgets, roadmaps, workflows, incentives, or decisions.

symptoms: Teams defend work by effort, tradition, ownership, or output volume rather than by purpose contribution.

symptoms: Metrics are optimized even when stakeholders suspect the underlying outcome is not improving.

symptoms: A system accumulates features, committees, reports, policies, or routines whose reason for existing is unclear.

symptoms: Purpose disputes are displaced into debates over tools, metrics, or priorities.

symptoms: The organization cannot tell the difference between success, activity, compliance, and survival of the process itself.

root_tension: The same means can be useful, efficient, profitable, measurable, or politically protected while no longer serving the end it was meant to advance. The intervention must preserve purpose without turning purpose into a vague slogan or a rigid excuse for suppressing adaptation.

anti_signatures: The problem is primarily that different actors have incompatible incentives or local goals; goal_congruence_alignment may be the better parent.

anti_signatures: The problem is primarily formal optimizer misspecification or reward hacking in a technical system; objective_function_alignment may be the closer neighbor.

anti_signatures: The work is only creating a vision or desired future without auditing current means; vision_to_action_alignment or backcasting_pathway_design may fit better.

anti_signatures: The problem is mistaken inference of intent from observed function, not redesigning means to serve a purpose; consider function_without_intent_caution.

anti_signatures: The purpose is not legitimately settled and affected parties have not been included; normative_assumption_explicitness or epistemic_inclusion_design should precede alignment.

structural_intervention: Define purpose/end state, map current means to purpose, identify misalignment, redesign means or metrics, and monitor purpose drift.

logic: State the purpose in a form that can guide choices, including who or what the purpose is for and what kind of end state would count as fulfillment.

logic: Convert the purpose into observable, qualitative, quantitative, temporal, or relational signs that the desired end state is being approached.

logic: Map current activities, roles, metrics, policies, functions, incentives, and decisions to the purpose they are supposed to serve.

logic: Identify means that are unsupported, obsolete, over-optimized, contradictory, or serving a proxy rather than the purpose.

logic: Change, remove, replace, constrain, or reweight means so the system better serves the end state.

logic: Install review signals and reopening conditions so purpose alignment can be revisited as context, scale, stakeholders, or evidence changes.

guidance: A consequential means should have an explicit, testable relation to the purpose or end state. If the relation cannot be stated, the means requires redesign, justification, or retirement.

guidance: A metric may represent the purpose only provisionally. If optimizing the metric predictably harms the end state, the metric must be treated as misaligned even if it improves measured performance.

guidance: If the stated purpose no longer fits the context, revise it through legitimate governance rather than quietly letting legacy means define purpose by inertia.

guidance: When multiple purposes are legitimate, define hierarchy, balancing rules, guardrails, or scope boundaries before declaring alignment.

guidance: A draft is incomplete unless it identifies what will change: a decision rule, metric, resource allocation, role, workflow, product behavior, or governance cadence.

description: The purpose must be specific enough to exclude some actions and prioritize others.

description: Every consequential means should be traceable to a purpose or explicitly marked as contested, obsolete, experimental, or transitional.

description: Metrics and targets must remain subordinate to the end state they approximate.

description: The purpose must be grounded in legitimate authority, stakeholder deliberation, mandate, ethical commitment, or design intent rather than imposed convenience.

description: The alignment judgment must be reopenable when evidence, context, scale, or affected parties change.

description: Teams can choose among competing activities by testing which better serves the end state.

description: Metrics and local targets are less likely to displace the purpose they were selected to support.

description: Legacy routines, features, reports, committees, or policies that no longer serve purpose can be redesigned or retired.

description: Decisions carry a visible rationale connecting them to the stated end state and can be reviewed later.

description: The system can detect when means begin to harden into ends-in-themselves.

prose_essence:
Purpose Alignment Design connects what a system is doing to what it is for. It is useful when a process, product, organization, policy, metric, role, or decision continues operating without a clear connection to the purpose or end state it is supposed to serve.

The archetype is not simply “having a purpose.” It is the intervention of making the purpose operational: defining the end state, mapping current means to that end, identifying drift or proxy substitution, changing consequential levers, and monitoring whether alignment holds over time.

prose_when_to_use:
Use this archetype when activity has become self-justifying. Common signs include features added because stakeholders request them, meetings preserved because they are traditional, metrics optimized because they are measurable, or policies defended because they are procedurally familiar even when their purpose is no longer being served.

It also fits when a team needs to choose among competing means and cannot decide responsibly until the end state is clear. If the purpose itself is contested or ethically suspect, use Normative Assumption Explicitness or Epistemic Inclusion Design first, then return to purpose alignment once the purpose has legitimate standing.

prose_structural_problem:
The structural problem is means-end drift. A means that once served a purpose can become an end in itself. A metric can replace the outcome it was meant to approximate. A role can survive after its function changes. A product can optimize engagement while failing the user outcome it claims to support.

This happens because systems accumulate inertia. Means are easier to see than ends; outputs are easier to measure than purpose; existing activity has owners and budgets; and proxy measures often become targets. Purpose Alignment Design interrupts that drift by asking: what is this for, what would it look like if it were working, and does this current means materially serve that end?

prose_intervention_logic:
The intervention begins by stating the purpose in a form that can actually guide decisions. It then translates that purpose into an end-state definition: recognizable signs that the purpose is being fulfilled. Next, it maps current means—activities, metrics, roles, workflows, features, incentives, and decisions—to that purpose.

Misalignment is diagnosed where a means has no clear connection to the end, where a proxy measure is being optimized at the expense of the end, where a legacy process survives by inertia, or where a local goal conflicts with the purpose. The intervention then selects redesign levers: changing metrics, workflows, decision rules, resources, incentives, role boundaries, or product behavior. Finally, it installs a purpose drift monitor so alignment can be revisited as context changes.

prose_key_components:
### Purpose Statement

A purpose statement names what the system, process, role, product, or policy is for. In this archetype, it is a component or artifact, not the whole intervention. A strong purpose statement constrains decisions; it can tell a team what to stop, refuse, prioritize, or redesign.

### End-State Definition

The end-state definition translates purpose into a recognizable condition. It may include quantitative indicators, qualitative evidence, stakeholder experience, system behavior, or ethical guardrails. Without this component, purpose language remains aspirational and cannot guide alignment.

### Means-Purpose Map

The means-purpose map connects current activities, decisions, metrics, roles, features, and resources to the purpose they are supposed to serve. It reveals which means are well-aligned, weakly justified, obsolete, contradictory, or serving a proxy rather than the end.

### Misalignment Diagnosis

Misalignment diagnosis identifies where purpose has drifted. Causes can include proxy optimization, legacy routines, local incentives, obsolete assumptions, unclear ownership, scale changes, or political protection of existing activity.

### Redesign Lever

A redesign lever is the consequential thing that will change: a metric, workflow, incentive, product behavior, role boundary, resource allocation, decision rule, or governance cadence. This component prevents the archetype from becoming a slogan exercise.

### Purpose Drift Monitor

A purpose drift monitor creates a signal or review cadence for asking whether the system is still serving its purpose. Drift monitoring matters because alignment can decay even after a good redesign.

prose_common_mechanisms:
### Purpose-to-Metric Mapping

Purpose-to-metric mapping is a method for translating purpose into measures and review questions. It implements the archetype when measurement is necessary, but it must preserve proxy humility: the metric is not the purpose.

### Mission Alignment Review

A mission alignment review is a governance ritual for checking programs, budgets, roles, or initiatives against mission. It is a mechanism, not the archetype itself, because the transferable pattern is the means-end alignment logic.

### Outcome-Driven Design

Outcome-driven design starts from the desired outcome and evaluates product, service, or policy choices by their contribution to that outcome. It implements the archetype in design settings.

### Function Analysis Workshop

A function analysis workshop asks what a part of the system currently does and whether that function still serves the purpose. It is useful for legacy roles, routines, processes, and institutions.

### Backcasting from Purpose

Backcasting from purpose starts with the desired end state and works backward to define milestones and pathways. It is one implementation of Purpose Alignment Design when the end is clear but the route is not.

### Goal Alignment Workshop

A goal alignment workshop helps teams compare local goals and activities against a shared purpose. It supports the archetype, but should not be confused with the archetype because workshops are only one implementation method.

### Product Purpose Review

A product purpose review checks whether features, roadmaps, growth targets, and success metrics continue to serve the product’s intended user or organizational outcome.

### Purpose-Clause Decision Record

A purpose-clause decision record documents which purpose a consequential decision is meant to serve. It makes later drift review possible.

prose_failure_modes: A common failure mode is purpose slogan substitution: the team writes inspiring language but changes nothing. Another is proxy metric capture, where the measure becomes the target. Purpose imposition occurs when leaders define purpose without legitimate participation from affected parties. Legacy means rationalization occurs when existing activity is retroactively justified. Single-purpose overreach happens when a complex system is forced into one purpose without balancing rules. Over-teleological explanation happens when observers infer intent from function; that is a cue to use Function-Without-Intent Caution instead.

prose_neighbor_distinctions: Purpose Alignment Design is distinct from Vision-to-Action Alignment because it does not only translate a vision into steps; it audits whether current means still serve the end. It differs from Goal Congruence Alignment because it is not only about actor incentives or local goals. It differs from Objective Function Alignment because it applies beyond formal optimizers and quantified objectives. It differs from Backcasting Pathway Design because backcasting is a possible mechanism, not the whole pattern. It differs from Normative Assumption Explicitness because value premises may need to be surfaced first, but purpose alignment then redesigns means around the accepted purpose.

prose_cross_domain_examples: In product design, a team removes features that increase engagement but do not improve the user outcome the product exists to support. In public policy, an agency redesigns paperwork because administrative convenience undermines timely access to benefits. In operations, a safety reporting system is revised when report volume becomes a compliance target rather than a learning signal. In AI governance, a ranking metric is checked against the intended human purpose and supplemented with guardrails. In education, assessments are redesigned when test preparation displaces deeper learning.

prose_non_examples: A mission statement refresh is not Purpose Alignment Design unless it changes decisions, metrics, or workflows. A pure causal mechanism map is not this archetype unless it is used to judge means-end alignment. Brainstorming a desired future is not enough without mapping current means. Inferring intent from observed function is not this archetype; it belongs closer to Function-Without-Intent Caution.

prose_tradeoffs:
Purpose clarity helps coordination but can oversimplify plural values. Metrics make alignment auditable but can substitute for meaning. Stable purpose prevents drift but may become rigid. Focus reduces waste but may suppress exploration. Review governance prevents drift but consumes time and political attention.

The archetype is strongest when these tradeoffs are explicit rather than hidden behind mission language.

prose_invariants_to_preserve: Preserve purpose specificity: the purpose must rule some actions in and others out. Preserve means-end traceability: consequential means should connect to the end state or be explicitly marked as contested. Preserve proxy humility: metrics are indicators, not the purpose itself. Preserve legitimate purpose source: alignment should not enforce an imposed or hidden purpose. Preserve reopenability: alignment must be revisited when evidence, context, scale, or affected parties change.

prose_target_outcomes: A successful application makes prioritization clearer, reduces proxy optimization, retires or redesigns misaligned activity, makes decisions more accountable, and detects purpose drift earlier. It should produce changes in actual means—metrics, workflows, incentives, resources, product behavior, or governance—not merely cleaner purpose language.

prose_parameter_dimensions:
Key tuning dimensions include purpose specificity, end-state measurability, review cadence, stakeholder inclusion, metric strength, redesign authority, and tolerance for plural purposes.

A narrow purpose increases focus but may suppress legitimate secondary ends. A broad purpose can include complexity but may fail to constrain decisions. Frequent reviews catch drift early but increase governance cost. Strong metrics improve accountability but increase proxy-capture risk. High redesign authority makes alignment consequential but can be dangerous if purpose legitimacy is weak.

prose_variants_and_near_names:
Metric-Purpose Alignment focuses on whether measurements and targets still represent the end state. Mission Alignment Review applies the pattern to organizations and portfolios. Product Purpose Alignment applies it to features, roadmaps, and user outcomes. Role-Function Alignment applies it to role design and responsibility boundaries. Purpose Drift Recovery applies it to mature systems whose original purpose has been displaced by inertia.

Near names include purpose alignment, means-end alignment, mission alignment, outcome alignment, goal alignment, objective alignment, and purpose-to-metric mapping. Some are aliases; others are mechanisms or neighboring patterns and should be routed carefully.

Metric-Purpose Alignment

short_definition: Aligns metrics and scorecards with the purpose they are supposed to approximate so measurement does not replace the end state.

distinctive_feature: The alignment problem is concentrated in proxy measures and objective functions rather than all activities.

distinct_from_parent: The parent can align any means or function with purpose; this variant focuses on measurement and metric substitution.

still_same_parent_because: The intervention still asks whether a means serves a purpose; the metric is simply the dominant means.

use_when: A quantified target is steering behavior but may no longer represent the purpose it was selected to serve.

use_when: Teams optimize dashboards, rankings, throughput, revenue, completion rates, or compliance counts at the expense of the underlying end.

domain: education

example: A school reviews whether test-score targets still serve learning, not only ranking or accountability compliance.

failure_modes: Replacing one bad proxy with another without defining the end state.

failure_modes: Treating a hard-to-measure purpose as invalid because it resists a single metric.

Mission Alignment Review Variant

short_definition: Applies purpose alignment to an organization, institution, program, or portfolio whose activities have drifted from mission.

distinctive_feature: The variant emphasizes governance, portfolio review, and institutional drift.

distinct_from_parent: The parent applies to any means-end structure; this variant focuses on organizational mission and resource allocation.

still_same_parent_because: It still clarifies purpose, maps means to purpose, diagnoses drift, and redesigns governance or activity.

use_when: Programs, meetings, budgets, or legacy commitments continue because they are established rather than because they serve mission.

use_when: Different teams invoke the same mission language to justify conflicting priorities.

domain: nonprofit governance

example: A board reviews whether funded programs still serve community outcomes rather than internal growth alone.

failure_modes: Mission language becomes a political shield for prior commitments rather than a standard for changing them.

Product Purpose Alignment

short_definition: Aligns product features, roadmaps, success metrics, and interaction design with the user or organizational purpose the product is meant to serve.

distinctive_feature: The variant centers on product functions and user outcomes.

distinct_from_parent: The parent is cross-domain; this variant speaks the language of features, roadmaps, usage metrics, and product reviews.

still_same_parent_because: It still maps means and functions to purpose, identifies misalignment, and redesigns the means.

source_primes: teleology function user_centered_design

use_when: A product roadmap accumulates features that serve growth, novelty, or stakeholder requests while diluting the product purpose.

use_when: Success metrics such as engagement, usage, or conversion may conflict with the purpose claimed for users.

domain: software product

example: A team cuts features that increase session time but do not improve the user outcome the product exists to produce.

failure_modes: Declaring user purpose while optimizing only growth or engagement metrics.

Role-Function Alignment

short_definition: Aligns roles, responsibilities, and decision authority with the function a role is supposed to serve in the larger system.

distinctive_feature: The alignment object is a role or responsibility boundary rather than a product, metric, or whole organization.

distinct_from_parent: The parent covers any means-purpose relation; this variant focuses on work design and authority-function fit.

still_same_parent_because: It still asks whether a structural means serves the end it exists to serve.

source_primes: teleology function goal_congruence

use_when: A role exists by tradition, hierarchy, or convenience but its function in the current system is unclear.

use_when: People are held accountable for outcomes without authority or resources tied to the role purpose.

domain: organizational design

example: A team revises a coordinator role after discovering the title no longer matches the decision support function needed by the system.

failure_modes: Using purpose language to expand role scope without clarifying constraints, authority, or nonpurpose boundaries.

Purpose Drift Recovery

short_definition: Restores alignment after a system that once served its purpose has drifted through proxy optimization, habit, scale, or environmental change.

distinctive_feature: The variant emphasizes temporal drift, review cadence, and recovery rather than initial design.

distinct_from_parent: The parent covers both initial alignment and redesign; this variant is specifically corrective and maintenance-oriented.

still_same_parent_because: The corrective work still follows the same purpose/end-state, means map, misalignment, redesign, and monitoring structure.

source_primes: teleology feedback adaptation

use_when: The original purpose may still be valid, but accumulated practices no longer serve it.

use_when: People defend current activity because it once made sense, even though conditions or outcomes have changed.

domain: operations

example: A reporting process created for safety learning is redesigned after it becomes a compliance ritual that discourages useful incident narratives.

failure_modes: Treating every drift signal as failure rather than distinguishing loss of alignment from legitimate purpose evolution.

near_names:
Purpose Alignment
Means-End Alignment
Mission Alignment
Goal Alignment
Objective Alignment
Outcome Alignment
Purpose-to-Metric Mapping
Product Purpose Review