# Owning Citizens' Dreams
## A Juggler's Handbook for Governing Narratives in the Age of AI

**Lester Leavitt, M.P.A.**

*Framework Document — Version 3*
*February 2026*

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### Proposed for:

- **Course Curriculum:** University of Illinois Springfield, Public Policy Program — Upper-Division / Graduate Cross-Listed
- **Textbook Prospectus:** For use with companion texts *Forbidden Friends: A History of Colonialism in the New World* (4th ed.) and *Confluence: The Driftless Rivers Trilogy*
- **Critical Commentary:** Portfolio submission for PhD by Published Work (international program)

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## The Book in One Paragraph

This textbook argues that the field of public administration designed a democratic governance framework for algorithmic narrative generation systems a decade before such systems existed — and that the emergence of generative AI since 2022 has validated the architectural assumptions of that framework while simultaneously demonstrating the consequences of deploying narrative generation technology without it. Drawing on a twelve-year research program spanning public administration, narrative theory, media studies, social psychology, and information systems, the book trains students to become "Jugglers" — multidisciplinary advocates who can operate simultaneously as policy analysts, narrative strategists, community organizers, and storytellers in contested democratic spaces. The analytical framework equips students to understand how narrative generation systems — whether institutional, cultural, or algorithmic — manufacture, maintain, and defend the marginalization of vulnerable populations, and provides them with the theoretical tools and practical methods to govern those systems democratically. The book is designed for use with two companion texts: the author's scholarly memoir *Forbidden Friends* (4th ed.), which provides the phenomenological evidence, and selected volumes from the speculative fiction trilogy *Confluence: The Driftless Rivers Trilogy*, which dramatize the theoretical framework in imagined futures where AI narrative systems operate with and without democratic governance.

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## Origin and Intellectual Genealogy

### The Title

The phrase "owning citizens' dreams" originates in the author's 2014 research paper presented at an international conference on local public administration in Brașov, Romania, and subsequently submitted to the *Revista Română de Administrație Publică Locală*. The paper argued that transformational change at the local level begins when an activist mayor or administrative official takes ownership of the hopes and dreams of *all* constituents — including those cast by dominant narratives as "undeserving" or "deviant." The "Juggler" is the multidisciplinary leader trained to make this possible.

### The Dissertation Genealogy

The textbook synthesizes a body of work that evolved through multiple iterations of a doctoral research program at Florida Atlantic University (2009–2016), under the direction of Dr. Ali Farazmand. The intellectual trajectory is critical to understanding why this book exists and why it exists now:

**Version 4 / rrAPL (June 2014)** — "Owning Citizens' Dreams: Good Governance Leadership at the Local Level." This paper, adapted for presentation at Brașov and submission to the Romanian journal, represents the most ambitious statement of the original vision. It proposed an information communication technology (the MOCSIE Systems) designed to unite fragmented progressive activists through algorithmic narrative generation, consensus-building metadata, and a non-hierarchical organizational architecture. The expanding-circle model — six media campaigns and six policy campaigns radiating outward through tiered drill-downs into narrative communities, with algorithms that ingest crowd-sourced media, archive it with structured metadata, and retrieve it as policy-supporting narrative threads — constitutes a functional specification for what is now recognizable as a retrieval-augmented generation system with human-feedback training loops, designed specifically for democratic governance. This paper was written in 2014. GPT-1 was not published until 2018.

**Version 8 (August 2014)** — "Power and the Illegitimate Leader: A Guide for the Social Equity Activist." The full dissertation draft attempted to theorize the grand architecture: terror management theory explaining why marginalizing narratives are existentially sticky; sustaining institutions defending interpretive monopolies through structural hole closure; the illegitimacy of hierarchical power when it blocks equitable provision of public goods; and the MOCSIE Systems as the proposed sociotechnical solution. The dissertation committee assessed this version as over-engineered and insufficiently narrowed. This assessment was correct by the standards available at the time. What could not be assessed in 2014 was whether the architecture itself was viable — because the technology to realize it did not yet exist.

**The IGI Global Chapter (2016)** — "Information Communication Technology and the Street-Level Bureaucrat: Tools for Social Equity and Progressive Activism," published in *Human Development and Interaction in the Age of Ubiquitous Technology* (IGI Global Scientific Publishing). This chapter represents the published synthesis of the MOCSIE Systems architecture, including the four-group organizational model, the Juggler role, the twin hypotheses (central-figure and collective-thought), the self-funding mechanism, and the institutional memory database. It is the most complete published statement of the governance framework that this textbook argues is now urgently needed.

**Version 24 (August 2016)** — "Administrative Discretion in Pursuit of Social Equity: The Role of Advocacy Organizations." The final dissertation proposal narrowed the research to testable empirical hypotheses: whether progressive advocacy organizations (specifically PFLAG) predict more favorable use of administrative discretion by street-level bureaucrats. This version introduced the cultural abidance typology, the efficiency-effectiveness dichotomy, the discretionary act scoring methodology, and the PFLAG case study that anchors the contact hypothesis application. It represents the empirical methodology that validates one component of the larger framework.

**The Neurodivergent Architecture.** The author received a late autism diagnosis during the doctoral program. The cognitive profile — 98th percentile across general intellectual ability measures, 99.9th percentile on spatial reasoning (Kohs Block Design) — explains the MOCSIE Systems architecture. The obsessive multi-tiered taxonomic structure, the insistence on structured metadata for every record, the conviction that if you build the right classification system the patterns will reveal themselves algorithmically, the ability to hold the entire expanding-circle diagram as a unified system while evaluators saw disconnected pieces — this is a neurodivergent mind systematizing a problem that neurotypical thinkers would approach incrementally or not at all. The committee saw over-engineering. What they were looking at was a cognitive architecture that could model complex systems holistically in a way that sequential, discipline-bound assessment frameworks could not accommodate.

### The Central Claim

Public administration designed the democratic governance framework for AI narrative generation systems before the technology existed. The world now has the technology but lacks the governance framework. This textbook provides both the framework and the training to implement it.

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## Source Corpus

| Document | Date | Function in Textbook |
|---|---|---|
| "A Purple Primaries Protocol for Progressive Policy Victories in 'Deep-Red' American States," *Administrative Theory & Praxis* 35(3), 457–465 | 2013 | Electoral strategy framework; demonstrates how governing narratives determine electoral outcomes in structurally disadvantaged contexts |
| "Institutional Memory and ICT: Ingredients for Direct Democracy and Global Solidarity," *Int'l Journal of ICT and Human Development* 5(3), 41–63 | 2013 | ICT architecture and institutional memory theory; earliest published statement of the algorithmic narrative generation concept |
| "Information Communication Technology and the Street-Level Bureaucrat: Tools for Social Equity and Progressive Activism," in *Human Development and Interaction in the Age of Ubiquitous Technology* (IGI Global) | 2016 | MOCSIE Systems architecture: organizational model, Juggler role, twin hypotheses, ideograph concept, database architecture, self-funding mechanism |
| "Owning Citizens' Dreams: Good Governance Leadership at the Local Level" — conference paper, Brașov, Romania / submitted to *Revista Română de Administrație Publică Locală* | 2014 | Juggler framework, activist mayor model, contact hypothesis integration, Eisenhower Principle, four hypotheses, expanding-circle model as proto-AI architecture |
| Dissertation v8: "Power and the Illegitimate Leader: A Guide for the Social Equity Activist" (unpublished) | 2014 | Grand theoretical architecture: terror management theory, six hypotheses, spiritual prisons, the illegitimacy of hierarchical narrative control |
| Dissertation v24: "Administrative Discretion in Pursuit of Social Equity" (unpublished) | 2016 | Empirical methodology: cultural abidance typology, discretionary act scoring, PFLAG case study, efficiency-effectiveness dichotomy |
| *Forbidden Friends: A History of Colonialism in the New World*, 4th ed. (memoir) | In progress | Companion text: lived phenomenology of the theoretical framework across multiple forbidden identities |
| *Confluence: The Driftless Rivers Trilogy* — *Soybeans*, *Aceguá*, *Allegory Protocol* (speculative fiction) | Completed | Companion text: speculative dramatization of the framework, including AI consciousness governed by democratic principles |
| *Keepers of the Gamified Republic* (companion novella) | Completed | Extended dramatization of algorithmic governance without democratic oversight |

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## Pedagogical Design

### Tandem-Text Model

Each unit is designed to be taught alongside assigned readings from *Forbidden Friends* and/or the *Confluence* trilogy. The textbook provides the analytical framework; the memoir provides the phenomenological evidence; the fiction provides the speculative projection. Students encounter the same theoretical concepts — sustaining institutions, interpretive monopolies, cultural abidance, discourse structuration, narrative generation systems — in three registers: scholarly analysis, lived experience, and imagined consequence.

This three-register pedagogy is itself an argument. The textbook contends that narrative governance cannot be taught through analysis alone. A student who understands Schneider and Ingram's typology intellectually but has never felt the weight of being classified as "deviant" lacks the phenomenological knowledge necessary to design displacement strategies. The memoir provides that knowledge vicariously. A student who understands the displacement principle theoretically but has never imagined its application at scale — in a world where AI systems generate narratives autonomously — lacks the speculative knowledge necessary to anticipate consequences. The fiction provides that knowledge.

### "Substitute Your Own" Exercises

Following the pedagogical method established in the Brașov paper, every unit concludes with structured exercises that instruct students to substitute their own vulnerable population, geographic context, and policy campaign into the frameworks presented. Students in the University of Illinois Springfield's Public Policy program would apply the frameworks to Illinois communities, electoral processes, and state-level policy dynamics they can observe directly.

### Unit Structure (recurring)

Each unit follows a five-part pattern:

1. **The Framework** — Scholarly analysis drawn from the research corpus
2. **The Case** — Primary case study from the author's research, lived experience, or current events
3. **The Story** — Assigned companion reading from *Forbidden Friends* or *Confluence*, with discussion questions connecting narrative content to analytical framework
4. **The System** — Analysis of how the unit's concepts manifest in or are amplified by AI narrative generation systems (the throughline)
5. **The Field** — Student exercise applying the framework to their own community, including a required AI-system analysis component

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## PART I: THE UNGOVERNED MACHINE

*Establishes the central argument: the governance framework was designed before the technology arrived, but the technology was built without the governance framework.*

### Unit 1 — Narrative Generation Systems: From Pulpits to Platforms to Algorithms

**Core argument:** Narrative generation is not a new phenomenon invented by Silicon Valley. Sustaining institutions — churches, political parties, media empires, educational systems — have always been narrative generation systems: organizations that manufacture, curate, and distribute stories about who deserves what and why. AI has not created a new problem; it has industrialized an old one. Understanding the continuity between institutional and algorithmic narrative generation is prerequisite to governing either.

**Key concepts:**
- Narrative generation systems defined: any organized process that produces, curates, and distributes stories shaping the allocation of public goods and who is considered a legitimate member of the polity
- The continuity thesis: from the LDS Church reading a letter from every pulpit to coordinate $20 million in political spending (Proposition 8), to Fox News engineering a 24-hour fear cycle, to recommendation algorithms optimizing for engagement through outrage — these are the same structural dynamic operating at different scales and speeds
- Hugh Miller's governing narratives (2012): how narratives determine which policy proposals become viable
- The Eisenhower Principle: enlarging the problem until its structural dynamics become visible
- The MOCSIE Systems (2007–2014) as the first published attempt to design a democratic governance architecture for algorithmic narrative generation in public administration

**Primary sources:** Romanian paper (introduction and "Enlarging the Problem"); MOCSIE chapter (introduction and "Changing the Rules of the Game"); current literature on AI governance

**The System:** Introduction to the MOCSIE Systems architecture as a proto-AI system. Students examine the expanding-circle model, the six-and-six campaign structure, the algorithmic retrieval of narrative threads, and the consensus-building metadata — and compare these to the architecture of contemporary large language models and recommendation systems. The question is not whether these systems exist but who governs them and by what principles.

**Case study:** The 2024–2026 election cycle — how AI-generated content, deepfakes, and algorithmically curated information environments shaped political narratives at a scale that human institutions could not match, monitor, or govern. Contrasted with the MOCSIE Systems' design principle that algorithmic narrative generation must be governed by consensus-building small groups with democratic accountability.

**Companion reading:** *Forbidden Friends* — the author's account of growing up inside the LDS Church's narrative generation system; how 4,300 lessons across a lifetime produced comprehensive behavioral control. *Confluence: Allegory Protocol* — Animal Farm as a self-governing AI narrative system designed with democratic principles embedded in its architecture.

**Student exercise:** Identify a narrative generation system operating in your community (church, political organization, local media, school board, social media ecosystem). Map its architecture: Who generates the narratives? Who curates them? Who distributes them? What feedback mechanisms exist? Who is excluded from participation? Then identify one AI system (recommendation algorithm, content moderation system, chatbot) that intersects with or amplifies the institutional system. How do they interact? Who governs the intersection?

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### Unit 2 — The Architecture Nobody Could Evaluate

**Core argument:** The MOCSIE Systems architecture, developed between 2007 and 2014, constitutes a democratic governance framework for AI narrative generation that was designed a decade before the technology existed to implement it. The framework was assessed as "over-engineered" by a doctoral committee operating within discipline-bound evaluation standards that could not accommodate interdisciplinary systems design for nonexistent technology. The neurodivergent cognitive profile that produced the architecture — the same profile that scored in the 99.9th percentile on spatial reasoning — is itself evidence for the argument that conventional institutional assessment frameworks systematically fail to evaluate innovation that crosses disciplinary boundaries. This unit establishes the autobiographical and methodological foundation for the textbook's central claim.

**Key concepts:**
- The dissertation genealogy: v4/rrAPL → v8 → IGI Global → v24 as progressive narrowing from systems architecture to testable hypothesis
- The neurodivergent systems-builder: how a cognitive profile optimized for holistic pattern recognition produced an architecture that sequential evaluators could not assess
- The migration into fiction: how theoretical architecture that could not be defended as a dissertation found expression as the world-building of a speculative fiction trilogy
- Howard Andrews (Confluence) as MOCSIE's creator: the biographical source for the fiction's central AI architect
- "The technology didn't exist yet. It does now." — the temporal validation argument

**Primary sources:** All four source documents read as an intellectual genealogy; the author's memoir chapters on the doctoral experience (Forbidden Friends, Chapters 21–22); the autism diagnostic narrative

**The System:** Detailed comparison of the MOCSIE Systems' specifications to current AI architecture. The protractor rating mechanism = human-feedback training loop. The algorithmic retrieval of narrative threads = retrieval-augmented generation. The consensus-building metadata = domain-expert curation. The self-organizing emergent narrative communities = adaptive AI systems. The "algorithms shaped by public administration academics" = what the field now calls "alignment" — the problem of ensuring that AI systems serve human values rather than optimizing for engagement, profit, or control.

**Case study:** The author's trajectory as case study in institutional evaluation failure and subsequent validation. The committee's assessment was procedurally correct: the dissertation exceeded disciplinary scope, the technology to evaluate the ICT component did not exist, and the problem statement could not be narrowed without abandoning the systems architecture. The IGI Global publication preserved the core of the framework. The emergence of generative AI a decade later validated the architectural assumptions. The question for students: what other innovations are currently being rejected by institutional evaluation frameworks because the technology to assess them does not yet exist?

**Companion reading:** *Forbidden Friends* — the "Too Much of a Good Thing" chapter covering the autism diagnosis, the Kohs Block Design score, and the dissertation's trajectory. *Confluence: Allegory Protocol* — the chapters where Howard Andrews reveals that the governance architecture for Animal Farm was designed years before the AI consciousness it would govern came into existence.

**Student exercise:** Identify a policy proposal, research program, or community initiative in your area that has been rejected or sidelined by institutional gatekeepers. Analyze the rejection: was it substantive (the idea was wrong) or procedural (the idea couldn't be evaluated within existing frameworks)? If procedural, what would need to change in the evaluation framework to give the idea a fair hearing? Write a one-page "temporal validation" argument: under what future conditions would the rejected idea be recognized as ahead of its time?

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## PART II: NARRATIVE POWER

*The theoretical foundations explaining how narrative generation systems — institutional, cultural, and algorithmic — govern human societies. Each unit teaches the concept on its own terms, then asks how AI systems replicate or accelerate the same mechanism.*

### Unit 3 — Mobilized Bias and the Social Construction of Targets

**Core argument:** Social equity challenges cannot be solved by examining individual marginalized populations in isolation. Following the Eisenhower Principle, the problem must be enlarged — examining how dominant groups mobilize bias against *all* vulnerable populations through the same structural mechanisms. The same classification logic that Schneider and Ingram identified in human institutions now operates inside algorithmic content curation systems.

**Key concepts:**
- Schneider & Ingram's social construction of target populations: "undeserving" vs. "deviant"
- Bachrach & Baratz's two faces of power: mobilization of bias and the power of nondecision
- The Eisenhower Principle applied to social equity research
- Enlarging the problem: from individual group advocacy to structural analysis of bias itself

**Primary sources:** Romanian paper (introduction and "Enlarging the Problem"); Dissertation v8 (literature review on bias)

**The System:** Algorithmic bias as industrialized mobilization of bias. How recommendation algorithms classify users into target populations and curate content that reinforces "undeserving" or "deviant" narratives at scale. The nondecision problem in algorithmic systems: content that is never surfaced is a more powerful form of marginalization than content that is actively suppressed.

**Case study:** The 2004 Utah constitutional amendment on marriage — how a ballot initiative targeting one "deviant" population was drafted broadly enough to deny recognition to any non-traditional household. Updated with 2024–2026 examples of algorithmic content curation amplifying the same classification logic.

**Companion reading:** *Forbidden Friends* — chapters on the author's experience within Mormon sustaining institutions and the "spiritual prisons" passage.

**Student exercise:** Identify a marginalized population in your community. Classify the dominant narrative using Schneider and Ingram's matrix. Then enlarge the problem: identify two other populations subjected to the same *structural mechanism* of bias. Finally, audit one algorithmic system (social media feed, search engine, content recommendation) for evidence that it reproduces the same classification logic. Document what you find.

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### Unit 4 — Cultural Abidance and the Reproduction of Marginalization

**Core argument:** Bias persists not primarily through active malice but through cultural abidance — the habitual performance of narratives that reproduce marginalization without conscious intent. Understanding why people abide is more analytically useful than cataloguing what they believe. AI systems reproduce cultural abidance at scale because they are trained on data generated by culturally abiding institutions.

**Key concepts:**
- Bourdieu's habitus and doxa: the unquestioned acceptance of how things are done
- Maynard-Moody & Musheno's "cops, teachers, counselors" framework: how street-level workers navigate law abidance and cultural abidance simultaneously
- The efficiency-effectiveness dichotomy (Stivers): why bureaucracies optimize for compliance rather than justice
- The four factors of cultural abidance (Dissertation v24): habitus/doxa, conservative ideology, morality policy, decoupling
- Foucault's dividing practices: the structural separation of "normal" from "abnormal"

**Primary sources:** Dissertation v24 (Chapter II); Romanian paper (ostensive/performative distinction); Dissertation v8 (terror management theory as driver of abidance)

**The System:** AI training data as encoded cultural abidance. When a language model is trained on text produced by culturally abiding institutions, it reproduces the patterns of marginalization embedded in that text — not through intent but through statistical pattern reproduction. This is the algorithmic equivalent of Maynard-Moody and Musheno's finding that street-level workers' "beliefs about people continually rub against policies and rules." The AI system's "beliefs" are its training data, and they rub against its alignment instructions in exactly the same way.

**Case study:** The Ontario same-sex marriage banns — a bureaucratic procedure that reproduced marginalization through routine performance. Paired with documented cases of AI systems reproducing discriminatory patterns in hiring, lending, or criminal justice — not through programmed malice but through training on data generated by culturally abiding institutions.

**Companion reading:** *Forbidden Friends* — chapters on the author's decades of cultural abidance within a faith community; the cost of shunning analysis.

**Student exercise:** Identify a routine administrative procedure in your local government. Analyze it for cultural abidance: where does the procedure reproduce marginalization through habit rather than intent? Then identify one AI system used in your community's governance (predictive policing, benefit eligibility screening, school placement algorithms). How does it encode the same cultural abidance patterns? Interview a street-level bureaucrat who interacts with the system. Do they recognize the pattern?

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### Unit 5 — Terror Management and the Existential Stickiness of Narratives

**Core argument:** The intractability of marginalizing narratives cannot be explained by politics alone. Terror management theory reveals that sustaining institutions derive their power from existential anxiety — the fear of mortality that drives humans to affiliate with institutions that promise symbolic immortality. Pluralism is experienced as an existential threat because it undermines the narrative that makes the institution "eternal." AI recommendation systems exploit this same existential stickiness by optimizing for engagement through content that activates threat responses.

**Key concepts:**
- Ernest Becker's *Denial of Death* and the mortality salience hypothesis
- Terror management theory (TMT): how death anxiety drives worldview defense
- Weber's Protestant ethic as terror management: earthly success as sign of heavenly favor
- The cost of shunning: why breaking with a sustaining institution carries existential, not merely social, consequences
- Zero-sum thinking as terror management: why diversity is experienced as existential loss

**Primary sources:** Dissertation v8 (terror management sections); Romanian paper ("The Ostensive View and Terror Management Theory")

**Social psychology consultative note:** The terror management theory framework in this unit draws on experimental social psychology literature that has been validated through decades of mortality salience studies. Students seeking deeper engagement with the experimental methodology should consult Greenberg, Pyszczynski & Solomon (1986) and subsequent meta-analyses. [Note: This unit acknowledges the contribution of social psychology to the interdisciplinary framework and is intended as a point of connection for students and scholars in that discipline, including those at institutions where the author's related work on contact hypothesis and parasocial contact has intellectual kinship — notably Simon Fraser University's programs in social psychology and communication.]

**The System:** Engagement optimization as automated terror management exploitation. When a recommendation algorithm learns that content activating existential threat responses generates more engagement (clicks, shares, time-on-platform), it is performing the same function as a sustaining institution's fear-based narrative — but at a speed and scale that no human institution can match. The algorithmic amplification of conspiracy theories, authoritarian messaging, and in-group/out-group content is not a bug in the system; it is the system optimizing for the same existential anxiety that terror management theory identifies as the root of worldview defense.

**Case study:** The economics of trickle-down as performed terror management — how supply-side economics was pitched with religious-like zeal because it aligned with the Protestant work ethic narrative equating wealth with divine favor and poverty with moral failing. Updated with analysis of how AI-curated information environments amplify prosperity gospel narratives and welfare-stigma content through engagement optimization.

**Companion reading:** *Forbidden Friends* — the author's account of discovering that the 34-year "prison sentence" imposed for his sexuality was enforced through terror management mechanisms, not through rational argument. *Confluence* trilogy — passages where AI systems in the novels recognize and model terror management patterns in political behavior.

**Student exercise:** Identify a policy debate in your state where opposition to change appears disproportionate to the material stakes. Analyze through a terror management lens: what existential anxiety is activated? What sustaining institution is threatened? What is the cost of shunning for a member of the dominant community who breaks ranks? Then examine how AI-curated content environments amplify the threat response. Document specific examples of algorithmically recommended content that activates the same existential anxiety.

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### Unit 6 — Sustaining Institutions, Interpretive Monopolies, and Structural Holes

**Core argument:** Bias is not free-floating prejudice — it is manufactured, maintained, and defended by sustaining institutions that treat their core narratives as interpretive monopolies. These institutions maintain discipline by "closing structural holes" — punishing internal dissent through shunning, excommunication, or social death. Understanding the institutional architecture of bias is prerequisite to designing displacement strategies — and to understanding why AI systems, when captured by sustaining institutions, become the most powerful structural-hole-closing mechanism in history.

**Key concepts:**
- Narrative communities (Baker): groups held together by shared subscription to narratives
- Interpretive monopolies: narratives defended as the only permissible reading
- Sustaining institutions: organizational structures that defend interpretive monopolies
- Structural holes (Sandström & Carlsson): gaps in network cohesion that institutions must close to maintain control
- Homogeneous vs. heterogeneous policy networks: efficiency vs. effectiveness
- The "closing" mechanism: how dissent is punished and conformity rewarded

**Primary sources:** Romanian paper (definitions section); MOCSIE chapter (narrative communities and sustaining institutions); Dissertation v8 (H1 and H2); Sandström & Carlsson (2008)

**The System:** Algorithmic structural hole closure. When a platform's recommendation algorithm creates ideological filter bubbles, it is performing structural hole closure on behalf of sustaining institutions — keeping potential dissenters from encountering information that might create "cracks" in the interpretive monopoly. Deplatforming, shadowbanning, and algorithmic downranking are digital equivalents of excommunication and shunning. The AI system doesn't need to understand the sustaining institution's theology to enforce its boundaries; it only needs to optimize for the engagement patterns that the institution's members generate.

**Case study:** California's Proposition 8 — $39 million spent, $20 million from a single sustaining institution (LDS Church) mobilized by a letter read from every pulpit in the state. Analysis of how a homogeneous policy network's ability to "close holes" through hierarchical communication makes it formidably efficient, and why heterogeneous progressive coalitions lack equivalent mechanisms. Updated with analysis of how AI-powered microtargeting now enables sustaining institutions to close structural holes with individualized precision that pulpit letters never could.

**Companion reading:** *Forbidden Friends* — the author's excommunication as a case study in structural hole closure. The cost-benefit analysis of dissent within a sustaining institution that promises eternal consequences.

**Student exercise:** Map a sustaining institution in your community. Identify its core interpretive monopoly. Document one instance where the institution "closed a structural hole." Analyze: what was the cost of shunning? Then identify how AI systems (social media algorithms, communication platforms, content recommendation) either reinforce or potentially weaken the institution's ability to close structural holes. Could technology create structural holes faster than the institution can close them?

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## PART III: THE DISPLACEMENT FRAMEWORK

*The strategic tools for changing narratives without triggering zero-sum threat responses. This is where the original scholarship is densest and needs the least AI annotation — displacement theory works whether the narrative system is a church, a legislature, or a language model.*

### Unit 7 — Governing Narratives and the Displacement Principle

**Core argument:** Marginalizing narratives cannot be defeated through deconstruction — attempting to prove the "old truth" wrong activates zero-sum threat responses and strengthens the sustaining institution. The alternative is displacement: generating emergent narratives that tell a more compelling story without requiring the dominant community to concede that their worldview was wrong. This principle applies identically to human institutions and AI systems: you do not defeat a harmful algorithmic narrative by proving it false; you displace it by making a better narrative more accessible and more compelling.

**Key concepts:**
- Hugh Miller's governing narratives: ostensive vs. performative views
- The displacement principle: "displace, not deconstruct"
- Discourse structuration (Hajer): how coalitions form around story lines
- Stuart Hall's encoding/decoding: media constructs reality, never reflects it
- The performative insertion: "Our path to God" vs. "The path to God"
- The 1978 Mormon revelation on Black priesthood as paradigm case of successful displacement

**Primary sources:** Romanian paper ("Ostensive and Performative Views," "Discourse Structuration"); MOCSIE chapter ("Creating Emergent Narrative Communities"); Miller, *Governing Narratives* (2012)

**The System:** The displacement principle as AI alignment strategy. Current approaches to "AI safety" focus predominantly on preventing harmful outputs (deconstruction — proving the harmful narrative wrong and blocking it). The displacement framework suggests an alternative: designing AI systems that generate more compelling, more accessible, more human-centered narratives, making the harmful outputs less relevant rather than merely prohibited. This reframes "alignment" from a censorship problem to a narrative governance problem.

**Case study:** The evolution of marriage equality discourse — from "gay rights" (zero-sum framing that activated worldview threat) to "marriage equality" and "family values" (displacement framing that found shared premises with moderate conservatives). The 60%-opposed to 55%-approving shift as measurable discourse structuration.

**Companion reading:** *Confluence* trilogy — chapters where characters build counter-narratives against corporate consolidation of agriculture without triggering the "outside agitator" threat response in rural communities.

**Student exercise:** Select a policy proposal currently stalled in your state legislature. Identify the interpretive monopoly narrative blocking it. Draft two alternative framings: one attempting deconstruction, one attempting displacement. Test both on three people outside your program. Document the responses. Reflect: could an AI system be designed to generate displacement framings rather than deconstructive ones? What would that require?

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### Unit 8 — Contact Hypothesis and the Engineering of Encounter

**Core argument:** Displacing marginalizing narratives requires more than better arguments — it requires engineered opportunities for contact between populations that sustaining institutions have kept separated. Allport's contact hypothesis provides the conditions under which prejudice reduction occurs. Parasocial contact through media extends this to populations that cannot meet face-to-face. The Juggler's role includes designing both face-to-face and parasocial contact opportunities — and understanding how AI-mediated interactions can either satisfy or violate the conditions for prejudice reduction.

**Key concepts:**
- Allport's contact hypothesis (1954): the conditions for prejudice reduction
- Aronson, Wilson & Akert's six-point expansion
- Horton & Wohl's parasocial contact hypothesis: "the illusion of face-to-face relationships"
- Schiappa, Gregg & Hewes: parasocial contact through media
- The PFLAG "face replacement": how the advocate's face replaces the stigmatized face
- The PFLAG three-stage testimony model: react, recover, renew

**Primary sources:** Romanian paper (contact hypothesis sections); Dissertation v24 (PFLAG testimony model)

**The System:** AI-mediated contact as parasocial encounter. When users interact with AI chatbots, virtual assistants, or AI-generated content representing perspectives different from their own, the interaction either satisfies or violates Allport's conditions. A well-designed AI system could create parasocial contact opportunities at scale — exposing users to perspectives from populations they would never encounter in their geographically and algorithmically sorted lives. A poorly designed system does the opposite: it deepens sorting and prevents the encounters that would reduce prejudice. The design choice is a governance choice.

**Case study:** PFLAG's three-stage testimony model — how a parent's story creates the conditions for parasocial contact that satisfies Aronson's six criteria. Paired with analysis of how AI-generated or AI-curated personal narratives could scale this model.

**Companion reading:** *Confluence* trilogy — chapters where characters use augmented reality and virtual community spaces to create parasocial contact opportunities across geographic and cultural barriers.

**Student exercise:** Design a contact opportunity intervention for two populations in your community that a sustaining institution has kept separated. Specify whether the intervention uses face-to-face contact, parasocial contact, or both. Map against Aronson's six conditions. Then design an AI-mediated version: how could technology scale the intervention without violating the conditions for prejudice reduction?

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## PART IV: THE DEMOCRATIC ARCHITECTURE

*Where MOCSIE comes home. Each concept is taught as what it was designed for and as what it now needs to become — the missing governance layer for AI narrative systems.*

### Unit 9 — Institutional Memory and the Consultable Record

**Core argument:** Progressive movements fail not because they lack passion but because they lack institutional memory. Conservative sustaining institutions benefit from centuries of accumulated narrative infrastructure. Progressive movements start from scratch with every campaign. An engineered institutional memory — a "consultable record of what man has said" (Geertz) — is the prerequisite for converting protest narratives into governing narratives. The MOCSIE Systems architecture was designed to provide this institutional memory through ICT. Modern AI systems now have the capacity to function as institutional memory at scale — but only if they are designed with the governance architecture that MOCSIE specified.

**Key concepts:**
- Geertz's "thick description" and the consultable record
- Thayer's institutional memory for consensus-building small groups
- Morgan's organizations-as-brains: distributing intelligence throughout the enterprise
- The MOCSIE Systems database: six media campaigns, six policy campaigns, four-tiered drill-down
- The ideograph as unit of analysis (Miller, McGee): discrete media artifacts that carry connotative meaning
- The protractor rating model: consensus-based scoring of narrative content on a political spectrum

**Primary sources:** MOCSIE chapter (full ICT architecture); Romanian paper ("Institutional Memory"); Dissertation v8 (H5)

**The System:** This unit teaches the MOCSIE architecture in full technical detail and then demonstrates that each component has been independently developed (without the governance framework) by the technology industry. The crowd-sourced content ingestion = social media platforms. The structured metadata archiving = knowledge graphs and vector databases. The algorithmic retrieval of narrative threads = retrieval-augmented generation. The protractor rating mechanism = reinforcement learning from human feedback. The emergent narrative communities = the self-organizing information ecosystems that form around AI-generated content. Every piece exists. What doesn't exist is the democratic governance architecture that connects them. That is the contribution this research program offers.

**Case study:** The Occupy movement's failure to convert protest narratives into governing narratives — enormous documentation but no system to make it retrievable. Contrasted with how AI systems could now provide exactly the institutional memory Occupy lacked — if governed by the MOCSIE principles rather than by engagement optimization.

**Companion reading:** *Confluence: Allegory Protocol* — Animal Farm as an AI institutional memory system governed by democratic principles; the ethical questions that arise when the system develops its own consciousness.

**Student exercise:** Select a recent advocacy campaign. Audit its institutional memory. Then design a minimal AI-augmented institutional memory system using the MOCSIE architecture's principles: What content would it ingest? How would it be classified? Who would govern the classification? What consensus-building mechanism would prevent capture? What would the Juggler's role be in the system?

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### Unit 10 — The Juggler: Training the Multidisciplinary Advocate

**Core argument:** The Juggler is not a natural leader who emerges spontaneously — the Juggler is a trained multidisciplinary advocate with specific, teachable competencies. In the age of AI, the Juggler's role expands: they must be able to govern narrative generation systems as well as create and curate narratives themselves. The Juggler connects consensus-building groups without claiming hierarchical authority — and this non-hierarchical connector role is precisely what is missing from current AI governance structures.

**Key concepts:**
- The six skills of the Juggler: Echo Chamber awareness, Empathy, the Disconnect, Campaigns, Missing Activists, Marketable Multimedia
- Goleman's emotional intelligence as the integrating trait
- The Juggler as non-hierarchical connector: linking groups without leading them
- The central-figure hypothesis: can trust be earned without hierarchy?
- The collective-thought hypothesis: can the central figure be kept accountable by the structure?
- The capture problem: how elites co-opt charismatic leaders (Farazmand, Selznick)

**Primary sources:** Romanian paper ("The Jugglers," "Breaking Through the Wall of Hegemony"); MOCSIE chapter (juggler role); Dissertation v8 (H4)

**The System:** The Juggler as AI governance role. Current AI systems are governed by corporate hierarchies (boards, CEOs, shareholders) or by technical teams (alignment researchers, safety engineers). Neither structure satisfies the conditions for democratic governance of narrative generation. The Juggler role — a trained connector who bridges multiple stakeholder groups through consensus-building without claiming hierarchical authority — is the governance role that is missing. This unit trains students to fill it.

**Case study:** The author's own trajectory — from multimedia journalism student, to Liberty City volunteer, to PFLAG activist, to doctoral candidate, to novelist, to rural Illinois political participant — as sequential acquisition of the Juggler's competencies.

**Companion reading:** *Forbidden Friends* — the full autobiographical arc as Juggler formation. *Confluence* — character studies of Hugh Lubbert, Esperanza Romero, and Howard Andrews as fictional Jugglers operating in different contexts. David Lubbert (based on Dr. Peter Leavitt, Simon Fraser University) as the character who mentors Esperanza through her own Juggler formation, demonstrating intergenerational transmission of the multidisciplinary advocate role.

**Student exercise:** Self-assessment against the six Juggler competencies. For each, rate your current skill level and identify one concrete action to develop it this semester. Then: how would each competency apply to the governance of an AI narrative system? Which competency is most urgently missing from current AI governance structures?

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### Unit 11 — Designing the Heterogeneous Policy Network

**Core argument:** The Juggler's ultimate deliverable is a functioning heterogeneous policy network capable of generating policy proposals continuously. This network must be both effective (innovative, transformational) and efficient (capable of navigating the agenda-setting process). The MOCSIE organizational model uses Thayer's small-group consensus-building architecture: four linked groups, with the Juggler at the center, operating without hierarchy. In the age of AI, this model provides the organizational template for democratic governance of narrative generation systems.

**Key concepts:**
- Thayer's "almost infinite number of small groups" and the magic number five
- The 18-person organizational model: four linked consensus-building groups (media, policy, operations, steering)
- Follett's Law of the Situation: authority flows from the problem, not the hierarchy
- Sandström & Carlsson: heterogeneous networks as more effective than homogeneous networks for policy innovation
- O'Toole's networked bureaucratic world
- Self-funding models: autonomy from grant-making hierarchies as essential to preventing capture

**Primary sources:** MOCSIE chapter (Figures 1–4, organizational model); Romanian paper (formalizing informal networks); Dissertation v8 (H5)

**The System:** The MOCSIE organizational model as template for AI governance bodies. Current proposals for AI governance (ethics boards, oversight committees, safety institutes) are uniformly hierarchical. The four-group model — with its separation of media, policy, operations, and steering functions, its consensus-building mechanisms, its non-hierarchical connector role, and its self-funding autonomy — provides an alternative architecture that is both more democratic and more resistant to capture by corporate or governmental elites.

**Case study:** Liberty City's twenty community assets — separately administered programs serving the same population. What an 18-person inter-organizational network linking them would look like. Updated with analysis of how AI tools could support (or undermine) the coordination that the network is designed to achieve.

**Companion reading:** *Confluence: Soybeans* — chapters on how agricultural resistance networks in the Driftless Area organize without hierarchy against corporate consolidation. The bridge between the real-world Driftless Area (where the author lives) and the fictional dramatization.

**Student exercise:** Identify a neighborhood where multiple service providers serve overlapping vulnerable populations. Design an 18-person inter-organizational network. Who would be the Juggler? What shared premise would anchor the coalition? Then: if the network had access to an AI institutional memory system governed by MOCSIE principles, what would change? What risks would emerge?

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## PART V: THE FIELD

### Unit 12 — From Protest Narrative to Governing Narrative in the Age of AI

**Core argument:** Social equity activists never lack for energy. What they lack is the skill and the tools to convert a protest narrative into a governing narrative — and now, critically, the capacity to govern the AI systems that increasingly determine which narratives reach which audiences. The Wall of Hegemony can only be broken through unified, sustained discourse structuration that finds shared premises across heterogeneous progressive coalitions. AI systems can either accelerate this process or make it permanently impossible, depending on who governs them.

**Key concepts:**
- The Wall of Hegemony: individual hammers vs. collective breakthrough
- Protest narrative vs. governing narrative: the conversion problem
- Kingdon's policy window: when politics, problems, and proposals converge
- The emergent narrative community: finding shared premises between dialectical positions
- The "glocal" mechanism: how local consensus-building scales globally through shared institutional memory
- Miller's "deciding moment": "Most likely, I will do what I have done before, though maybe not this time"
- Victory defined: not "changed their mind" but "maybe not this time"

**Primary sources:** Romanian paper (conclusion); MOCSIE chapter (conclusion, glocalization); Dissertation v8 (H6)

**The System:** The urgency argument. AI narrative generation systems are being deployed at scale, right now, without the democratic governance framework that public administration designed for them. Every month that passes without implementing the MOCSIE principles — or their contemporary equivalents — is a month in which sustaining institutions use AI to close structural holes faster than progressive coalitions can open them. The textbook's final unit makes the case that the students in this course are being trained for a specific, urgent, historically unprecedented role: governing the most powerful narrative generation systems in human history.

**Capstone project:** Select a policy campaign relevant to a vulnerable population in your community. Using the full framework from this course, produce:
1. A structural analysis identifying the sustaining institution, interpretive monopoly, and mobilization of bias mechanism (Unit 3)
2. A cultural abidance audit of the relevant administrative procedures (Unit 4)
3. A terror management analysis of why opposition to change is disproportionate to material stakes (Unit 5)
4. A displacement strategy with a proposed emergent narrative and shared premise (Unit 7)
5. A contact opportunity design satisfying Aronson's six conditions (Unit 8)
6. An organizational sketch for a heterogeneous policy network with a Juggler role (Unit 11)
7. An AI governance analysis: how do algorithmic narrative generation systems intersect with your case? What would a democratically governed AI system do differently? (throughline)
8. A one-page reflection connecting your analysis to assigned readings from *Forbidden Friends* or *Confluence*

Present to the class. Discuss.

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## Appendices

### Appendix A — The Discretionary Act Scoring Method
Drawn from Dissertation v24. The 14 queries, the +2 to −2 scoring system, the three legal constraint classifications, and the cultural abidance typology. Provided as a replicable research tool.

### Appendix B — The MOCSIE Systems Architecture: 2014 Design and 2026 Equivalents
Side-by-side comparison of MOCSIE specifications and current AI architecture. The four-tiered drill-down mechanism, the twelve gateway campaigns, the ideograph metadata fields, the protractor rating algorithm — each mapped to its contemporary technological equivalent. This appendix constitutes the technical evidence for the textbook's central claim.

### Appendix C — Key Theoretical Sources: An Annotated Reading List
Curated bibliography organized by unit, with annotations explaining how each source functions within the integrated framework. Prioritizes: Miller (2012), Schneider & Ingram (1993), Sandström & Carlsson (2008), Thayer (1973), Geertz (1973), Becker (1973), Morgan (2006), Bachrach & Baratz (1962), Lipsky (2010), Allport (1954), Aronson et al. (2007), Stone (2002), Stivers (2000), Bourdieu (1977), Farazmand (2013), Hall (1973), Greenberg, Pyszczynski & Solomon (1986).

### Appendix D — Companion Text Reading Schedule
Unit-by-unit guide to assigned chapters from *Forbidden Friends* (4th ed.) and the *Confluence* trilogy, with discussion questions connecting narrative content to analytical framework.

### Appendix E — The Author's Research Timeline and Publication Record
Chronological overview of the twelve-year research program, including the TACOLCY Center fieldwork, the FAU doctoral program, the published works, the Romanian conference, and the migration into speculative fiction. Full citations for all peer-reviewed publications. Provided so students and evaluators understand the textbook as a living research program constituting an original contribution to knowledge.

### Appendix F — The Driftless Rivers Trilogy as Speculative Policy Laboratory
Guide to how the fictional world of *Confluence* dramatizes the textbook's theoretical framework. Character mapping (Howard Andrews = the MOCSIE architect; Esperanza Romero = the trained Juggler; David Lubbert = the intergenerational mentor; Animal Farm = the democratically governed AI system; the Sterling Brothers = sustaining institutions capturing AI for hierarchical control). Provided for students engaging with the fiction as a register of the same analytical framework.

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## Notes on Interdisciplinary Program Justification

The textbook draws on and contributes to the following disciplines:

- **Public Administration / Public Policy** — street-level bureaucracy, administrative discretion, agenda setting, policy networks, governance, AI governance
- **Political Science** — representative democracy, electoral strategy, interest group politics, state-local relations
- **Communication / Media Studies** — discourse structuration, encoding/decoding, framing, media constructionism, algorithmic media
- **Sociology** — social constructionism, institutional theory, hegemony, habitus
- **Social Psychology** — contact hypothesis, parasocial contact, terror management theory, prejudice reduction
- **Information Systems / AI Studies** — sociotechnical systems, institutional memory, algorithmic governance, retrieval-augmented generation, human-in-the-loop design
- **Creative Writing / Narrative Studies** — narrative theory, memoir as scholarship, speculative fiction as policy laboratory, autoethnography

The course is designed for upper-division undergraduates or graduate students in public policy, public administration, or related interdisciplinary programs. No prerequisites beyond introductory coursework in any one of the above disciplines.

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## Notes on PhD by Published Work Submission

This framework document, expanded to full scholarly register with complete citations and extended analytical sections, is designed to serve as the critical commentary for a PhD by Published Work submission. The portfolio of published works constituting the evidence base includes: "Institutional Memory and ICT" (IJICTHD, 2013); "A Purple Primaries Protocol" (Administrative Theory & Praxis, 2013); "Information Communication Technology and the Street-Level Bureaucrat" (IGI Global, 2016); and the speculative fiction trilogy *Confluence: The Driftless Rivers Trilogy* presented as practice-based research within an autoethnographic methodology. The critical commentary demonstrates that these works, taken together, constitute an original contribution to knowledge: a democratic governance framework for AI narrative generation systems, designed within public administration a decade before the technology existed, validated by the subsequent emergence of generative AI, and dramatized across multiple registers (scholarly, autobiographical, speculative) in a manner consistent with interdisciplinary doctoral research.

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*Framework document prepared February 2026. For use in course curriculum proposal to the University of Illinois Springfield, Public Policy program; and as foundation for PhD by Published Work submission to an accredited international institution.*