Post-Hierarchy Glossary

A decision and coordination architecture in which the right to define a problem, shape a decision, and influence it is not automatically and permanently concentrated in a single office, committee, or institution.

Post-hierarchy does not mean abolishing structure, leadership, or accountability. It separates formal responsibility for implementation from an epistemic monopoly over decision-making: temporary configurations of competence form around a specific problem, while influence arises from relevant competence, reliable contribution, and collective interaction. When the work is complete, the group disperses; results and a memory of contribution remain, but no permanent centre of authority should emerge.

An organised and iterative process of diagnosing a problem, generating ideas, evaluating them, forming solutions, monitoring their implementation, and, when necessary, reopening the decision process.

Decidement is broader than voting, consultation, or ordinary brainstorming. It includes discovering the structure of a problem, generating alternatives, anonymous evaluation, separating new questions, identifying specializations, accounting for contribution, forming resolutions, and feeding implementation results back into the process. A decision is treated not as the end of the process but as the beginning of another learning cycle whenever reality produces new evidence.

A full participant in collective decidement who may evaluate the ideas of others, submit solutions of their own, and contribute to the collective result according to their relevant competence.

A brainstormer does not hold a universal expert title. The participant accumulates different specialization weights through real contribution in previous projects, so influence is contextual rather than status-based. In a new application, sufficient weight in a relevant specialization may allow direct entry as a brainstormer; otherwise the applicant-and-candidate pathway applies.

A temporary collective-decision environment created around a specific application, problem, or field of decision.

Several decision projects may operate within a cluster either simultaneously or sequentially. Participants may change and join during the process, while new questions may generate new projects or be transferred to other groups. The cluster closes when its tasks have been resolved, transferred, or no longer justify continued work. A cluster is not a standing committee or a permanent organisational unit.

A distinct task within a cluster in which ideas addressing a specific problem or question are generated and evaluated anonymously.

A single cluster may contain many interconnected projects. New projects can emerge from earlier results, discovered contradictions, or missing knowledge. If a question requires a substantially different configuration of specializations, it may be transferred beyond the current cluster. Each submitted idea should, as far as possible, be self-contained and independently evaluable.

A cognitive and practical field of competence describing what kinds of knowledge, experience, or capability actually mattered in a particular decision project.

A specialization is not merely a diploma, job position, or professional title. It is usually not fixed conclusively before the project begins: AI may initially provide orientation, while participants can later propose more precise descriptions of the specializations involved and evaluate their importance. The system thus links competence to work actually performed rather than to permanent status.

A collective indicator of how important a particular specialization was to the outcome of a specific decision project.

This weight is not a participant's self-assessment. It emerges from collective evaluation and connects the content of the project with participants' actual contribution. The more important a specialization is to a particular result, the more strongly it affects the updating of the relevant participants' specialization weights.

An indicator of a participant's accumulated reliable contribution within a particular specialization, describing their functional competence in that field.

A person may hold many different specialization weights earned across different clusters. A new application uses only the relevant part of that history. Weight grows according to real contribution and the importance of the specialization in the project, but it must not turn into a permanent expert rank or title of authority.

A principle under which each additional reliable contribution increases an already high specialization weight by progressively less.

Saturation protects the system from a new oligarchy: early participation does not become permanent privilege, strong newcomers can approach established participants, and a few veterans cannot gradually monopolise the collective result. Weight may also decline after prolonged inactivity or as a field itself changes.

A sufficient combination of participants' relevant specialization weights, their diversity, and their complementarity to begin competent collective work on a particular project.

This is not a headcount. A small but complementary group of strong specializations may have greater cognitive capacity than a large crowd poorly matched to the problem. At the beginning, relevance may be estimated using AI-generated orientation, but the project's actual competence structure can be refined as the work develops.

A person who wants to participate in a cluster but does not have enough system-recorded history in relevant specializations to enter immediately as a brainstormer.

AI may generate questions for the applicant from the thematic core of the application and its important periphery. The purpose is not to grant a formal certificate but to test whether the person understands the problem field well enough to move to the next stage of participation.

An indicator summarising how well an applicant understands the subject matter of the application and the peripheral dimensions relevant to decidement.

The test may examine factual knowledge, degrees of correctness, false premises, technological feasibility, cost, risks, causal relationships, and other dimensions important to the application. A sufficient result allows progression to candidate status but does not in itself confer permanent expert status.

The ability to judge one's own limits of knowledge, uncertainty, and the probability that an answer or evaluation may be wrong.

Epistemic calibration is an additional rather than primary signal of competence. Tests may include options such as 'I don't know', 'None of the answers is correct', or 'All answers are correct', as well as questions built on false premises. The purpose is to distinguish genuine understanding from unwarranted confidence.

An applicant who has reached a sufficient knowledge score and has been admitted to evaluate real cluster ideas in shadow mode.

A candidate cannot yet submit solutions of their own, and their evaluations do not affect the collective result. Their real evaluation profile is used to determine whether the person can judge reliably in a live decidement environment and can progress to brainstormer status.

A candidate's real evaluation of an idea that the system records and analyses but does not yet include in the calculation of the collective result.

Shadow mode makes it possible to test a person's evaluation model in real decidement without granting an unvalidated participant direct influence over the shared outcome. Competence is therefore tested not only through a knowledge test but also through behaviour toward real ideas.

The sequence and structure of many idea evaluations made by the same participant, allowing a relatively stable mental model of evaluation to be identified.

A candidate's profile does not have to replicate the majority. It should show a reliable relationship with competent evaluation patterns, especially where brainstormers with high weight in relevant specializations exist. Individual deviations are not automatically errors; they may be sources of new insight.

A scale from −5 to +5 used to evaluate an individual idea rather than an entire project, its author, or an application.

Positive scores indicate agreement and negative scores disagreement. Extreme −5 and +5 ratings are possible but should be reserved for exceptional cases. Zero is not the neutral midpoint of this scale: it is reserved for diagnostic rejection when an idea is unsuitable for ordinary collective ranking.

A diagnostic code indicating that a submitted idea is unsuitable for ordinary collective ranking and should not consume further collective attention.

A score of 0 may be used when an idea duplicates another, combines several separately evaluable claims in one submission, is banal, falls outside the project's topic, is unintelligible, or reveals its author. −5 still means very strong disagreement with a meaningful and evaluable idea; 0 belongs to a different diagnostic category.

A regime in which the system knows a participant's identity and records their actions, while other participants do not see the authors of ideas and need not know the full composition of the group.

Anonymity reduces the influence of status, reputation, personal relationships, and interest pressure on evaluation, while accountability allows the system to preserve competence history, reward contribution, and apply rules of responsibility. This is not unaccountable anonymity: identity is hidden from other participants, not from the system itself.

A platform-recorded unit that a participant may accumulate for valuable contribution to the collective-intelligence process.

CI currency is one instrument for accounting for contribution and motivation alongside specialization weights and possible financial compensation. It may record created value, but it is not a formal title of authority and does not by itself confer a right to control future decisions.

The capacity of an interacting group to create an understanding of a problem or solutions that none of its individual participants possessed before interaction.

Collective intelligence is not a survey, a sum of votes, a consultation, or an aggregation of separately formed opinions. It emerges when some participants' ideas change what others can notice, evaluate, and propose, while this interaction generates new solutions, questions, or a new structure of the problem. Participation becomes collective intelligence only when interaction can change the shared outcome.

An initially unknown shared reference point of evaluation that emerges from competent, weighted, and interacting evaluations.

Collective wisdom is not known in advance and is not simply the majority position. A rational participant's strategy is not to push a private interest but to predict as accurately as possible which ideas will be recognised as strongest after interaction within a competent group. This aligns individual judgement with an attempt to 'hit the collective wisdom'.

A decision to transfer a problem that has emerged within one cluster to another group because it requires a substantially different configuration of specializations.

Participants or AI may propose a transfer. If the group agrees, work on that question closes in the current cluster and the problem may be transferred to another cluster or a new one may be created for it. In this way, a group does not pretend to be competent where its cognitive capacity is insufficient.

A clearly formulated outcome of cluster work specifying what should happen next with the application or with one of its questions.

A resolution may call for continuation, revision, funding, an experiment, additional conditions, transfer to another group, termination, or another next step. A resolution is not an immutable verdict: if implementation produces significant new evidence, the question may return to a new decidement cycle.

The dynamically changing set of people who participate in analysing an application or problem during the lifetime of a particular cluster.

New participants may join, members may take part in different projects, and under accountable anonymity they do not need to know the group's full composition. When the cluster closes, the group disperses; results and the memory of individual contribution remain, but no standing committee does.

An evaluation structure in which a competent group divides into two or more clearly distinct positions.

Polarization is not automatically evidence of a weak project or failed communication. It may reveal a deep and unresolved fault line in the problem, different assumptions, or competing values. In such cases polarization itself becomes information and may justify a new decision project.

A situation in which an idea or solution is strongly recognised across several different specializations, experiences, or perspectives on the problem.

Resonance helps reveal ideas that connect previously separate dimensions of a problem. It is not the same as popularity or a majority vote: what matters especially is whether people with different competences independently evaluate the idea strongly.

Interaction among different subjective perspectives in which shared understanding emerges not by eliminating individual viewpoints but by allowing them to complement, refine, and transform one another.

In a collective-intelligence environment, intersubjectivity is a source of synergy: one participant's anonymous idea may reveal a dimension others had not seen, while their responses can generate new solutions. Common ground arises through interaction rather than enforced uniformity.

An asymmetry in a decision system in which the right to define the problem, select relevant knowledge, interpret facts, and legitimise the decision depends on institutional position.

An epistemic hierarchy can exist even where people are formally consulted or invited to speak. The crucial question is whose knowledge can actually change the structure of the decision. Post-hierarchy seeks to detach this privilege from office and distribute influence according to relevant competence, experience, and the process of collective decidement.

Influence over a decision that arises primarily from office, title, rank, reputation, or institutional position rather than from contribution relevant to the particular problem.

Post-hierarchy does not mean that experienced or trusted people lose influence. It requires influence to be continually justified in the context of the problem. A teacher, manager, expert, or institutional leader may be an important participant, but their position should not automatically make their statement stronger than statements made by others.

A person's problem-specific capacity to provide a reliable evaluation or valuable solution regardless of their general status or position.

Functional competence is always contextual: the same person may be highly important in one decidement process and peripheral in another. It may rest on professional knowledge, accumulated experience, specialization weight, or other reliable signals. The concept distinguishes 'who is an expert in general' from 'who is competent for this question'.

Knowledge and evaluative capacity arising from direct experience of living with a problem, using a service, working inside a process, or experiencing the consequences of a decision.

A patient may know what a healthcare administrator cannot see; a student may know what a school leader cannot see; a city resident may know what an aggregate statistical indicator does not reveal. Experiential competence does not replace technical or professional competence, but complements it and may expose dimensions of a problem that would otherwise remain invisible.

A group of people whose living conditions, opportunities, rights, risks, or everyday experience are materially changed by the decision under consideration.

An affected group does not automatically own the decision, and its position is not automatically correct, but its experience is a relevant source of knowledge for decidement. In a post-hierarchical architecture, a channel must exist through which affected people's knowledge can genuinely change the formulation of the problem and the resulting solutions rather than remain a symbolic consultation.

A group or community that, through organised interaction, can form a shared understanding of a problem, produce solutions, and sustain action rather than merely aggregate individual opinions.

A city, school, professional community, or other group does not become a collective subject simply by having many members. It requires an infrastructure in which participants can see, evaluate, and extend one another's ideas and create a new shared outcome from them. The will of a collective subject is not given in advance; it emerges through the process.

A principle under which formal legal or administrative responsibility for an action does not grant one person or institution the exclusive right to formulate the decision itself.

A manager, physician, municipality, or other institution may remain responsible for implementation, legality, and safety, while the epistemic content of the decision is formed through a broader competent decidement process. Post-hierarchy therefore does not abolish accountability; it prevents accountability from automatically becoming an epistemic monopoly.

A mode of decidement in which a decision is treated as a testable intervention and its consequences are systematically fed into the next cycle of evaluation and correction.

In complex systems, not all consequences can be predicted accurately in advance. Implementation therefore becomes part of learning: observable indicators are defined, results are collected, unintended consequences are recorded, and a new project is formed when necessary. Adaptive decidement replaces the one-off model of 'we decided' with a continuing cycle of 'decide – test – learn – adjust'.

Collective decidement on questions where factual knowledge alone is insufficient because competing values, norms, duties, or moral principles must be reconciled.

Normative decidement does not replace values with majority voting. Its task is to expose competing assumptions, consequences, and principles; allow different competences and moral perspectives to interact; and seek a solution that best withstands collective evaluation. It is especially important in ethics, war, care, education, and other fields where facts alone do not determine what ought to be done.

A situation in which one person, office, expert group, or institution effectively controls the formulation of the problem, the selection of admissible knowledge, and the legitimisation of the final decision.

An epistemic monopoly is an extreme form of epistemic hierarchy. It may survive even where public consultation exists if other participants' contributions have no real capacity to alter the structure of the decision. Post-hierarchical architecture seeks to break such monopolies not through simple majority voting but through diversity of competence, accountable anonymity, interaction, weighted evaluation, and feedback.