Theory of Change — From Personal Pain to Transforming Urban Design

This note covers the social impact design component of the Quiet City Project. For audience design, see For Whom and What Do We Change?. For organizational design, see Separating Public Interest and Revenue (forthcoming).

Why a Logic Model Is Necessary

"I started because I wanted to reduce my own stress. Before I knew it, I was changing the city."

This statement is both an aspiration and a design objective. To move from personal pain to changing societal structures, emotion alone is insufficient. A blueprint that specifies which activities trigger which changes in which sequence is required. That is a logic model (ロジックモデル).

Personal Starting Point

The origin of this project is not an interest in social issues but the everyday experience of depletion as someone living with misophonia (ミソフォニア) and light sensitivity. The recognition that "invisible suffering" in the urban sound environment is neither visualized nor reflected in design or policy is the fundamental motivation underlying the entire project.

Logic Model: Five-Layer Structure

Input

• Personal lived experience (insider knowledge from living with misophonia and light sensitivity)
• The organizational foundation and public-interest credibility of the Institute for Social Vision and Design (ISVD)
• Correlate Design's capabilities in design, UI, and technology
• Student interns (Bunkyo Ward is a university-dense area)
• Existing research literature and technical infrastructure (TinyML, WHO noise guidelines, etc.)
• Knowledge from precedent cases (SoundPrint, KultureCity, the Hong Kong GPS study, etc.)

Activities

Phase 0 (Spring-Summer 2026)

• Fieldwork by Naoya himself (Hongo to Hakusan area, time-stratified walking logs)
• Interviews with 5-10 individuals with sensory hypersensitivity or misophonia
• Complaint gap survey (identifying "concerns not reaching local government")
• Structural analysis of noise regulation

Phase 1 (Autumn 2026 - Spring 2027)

• Construction of a low-cost sensor network (TinyML + Raspberry Pi)
• Launch of citizen-participatory data collection
• Empirical measurement of zoning x noise inequality
• Initiation of academic collaborations

Phase 2 (2027 onward)

• Publication of a real-time noise map (with quiet route suggestion functionality)
• Preparation and release of policy recommendation reports
• Development of B2B / B2G services

Outputs

• Noise x sensory stress dataset (Bunkyo Ward) --- published as open data
• Real-time noise map (with quiet route suggestion functionality)
• "Quiet City Report" series
• Policy recommendation report (regulatory structural analysis + environmental justice evidence)
• Academic papers (co-authored, peer-reviewed)
• Visualization report on disability x income x noise inequality

Short-term Outcomes

• Sensory-hypersensitive individuals and those with misophonia can choose their own walking routes for the day
• The existence of "people who cannot file complaints" becomes visible to the administration
• "Quietness" begins to gain recognition as a new evaluative criterion in real estate and urban design
• Structural gaps in noise regulation enter the policy discourse

Long-term Impact

• A society in which sensory-hypersensitive individuals can live ordinary lives in cities
• Noise inequality (low-income x disability x arterial roads) becomes established as a policy issue
• A "Sensory Stress Urban Index" becomes a standard metric for urban evaluation
• Starting from sound and extending to light --- completion of a platform covering all sensory stress

Theory of Change

"The reason urban sound environments do not change is that the suffering of those who are struggling is not visible. If it becomes visible, people will act. Therefore, we start by making it visible."

This single statement is the causal hypothesis running through the entire project, and we design the following five stages through which change occurs.

1. Transform personal experience into quantitative and qualitative data
2. Data becomes collective fact (one person's impression --> a pattern across 1,000 people)
3. Collective fact is translated into policy language
4. Policy changes urban design standards
5. Changed standards expand individual choices

The final step loops back to the first --- as individual choices expand, more people contribute data, and the cycle accelerates.

Risks and Assumptions

This logic model rests on several assumptions. We must also design responses for when these assumptions break down.

Assumption 1: Data will move policy --- The most precarious assumption. There are countless cases where data existed yet policy did not move. To mitigate this risk, we will build relationships with data "recipients" (administrative officials, legislators, media) in parallel from Phase 0 onward. Data must not only be produced but designed to be delivered.

Assumption 2: Sensory-hypersensitive individuals will participate in data collection --- For sensory-hypersensitive individuals, outdoor fieldwork is itself a source of stress. Design that lowers the participation threshold (short-duration protocols, the ability to withdraw at any time, compensation design) is essential. Recruitment cannot succeed without building trust with communities of affected individuals.

Assumption 3: The technical infrastructure will function --- There is a possibility that TinyML-based noise classification, wearable sensors, or GIS integration may encounter technical failures. A minimum viable technical validation (MVP) will be completed in Phase 0, and the decision to proceed to Phase 1 will be made on a data-driven basis.

References

Environmental Noise Guidelines for the European Region

World Health Organization (WHO). WHO Regional Office for Europe

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Using Theory of Change for programme design and evaluation

Vogel, I.. UK Department for International Development (DFID)

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The Curb-Cut Effect

Blackwell, A. G.. Stanford Social Innovation Review

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