By Jason F. Kronemeyer

Michigan’s Inclusive Training, Technology and Equity Network has an important word hiding in plain sight.

Network.

It is easy to think of MITTEN primarily as a grant program. In its current form, Michigan’s Inclusive Training, Technology and Equity Network establishes regional resource hubs intended to support digital inclusion through services such as digital skills training, device distribution, online accessibility, and access to affordable broadband. In 2025, the Michigan High-Speed Internet Office awarded nearly $10.6 million to 13 organizations to operate these regional hubs. [^1]

That work matters. Michigan’s own statewide engagement found residents facing barriers involving internet availability and affordability, devices, digital skills, and even knowing where to find appropriate resources or trained people who could help. MITTEN emerged in part as a response to those findings. [^2]

But if MITTEN is ultimately about building capacity, we should pay much more attention to what it means to build a network.

A network is different from a collection of programs. It is different from a directory of organizations. It is even different from a partnership.

A network has structure. It has nodes and relationships. Things move through it. Some parts are densely connected while others remain isolated. Some organizations become bridges between communities. Some people occupy positions where they routinely encounter information that never reaches others. Some opportunities travel widely, while others remain trapped within a small circle.

Network science gives us a way to understand these relationships, and I believe it also gives Michigan a powerful way to think about the next generation of regional digital opportunity.

Communities Are Already Networks

At its simplest, network science represents a network as a graph:

\[G = (V,E)\]

where $V$ represents nodes and $E$ represents the relationships, or edges, between them. Network scientist M. E. J. Newman showed how community structure can be characterized mathematically through modularity: networks can contain groups with relatively dense internal connections and comparatively sparse connections between groups. 1

In community development, those nodes are not abstract mathematical objects. They are people, libraries, schools, businesses, Tribal nations, colleges, local governments, nonprofits, healthcare providers, economic-development organizations, researchers, projects, resources, skills, and opportunities.

The edges connect them.

A resident knows a librarian. A school works with an employer. A township collaborates with a regional planning agency. A technician knows a manufacturer. A researcher works with a community organization. A business participates in a workforce program.

Viewed this way, community development is partly a network problem:

Who is connected to whom, what moves across those connections, and where are consequential connections missing?

That last question is particularly important.

Often the problem is not that our communities lack resources. It is that the people who need them are separated from the people who have them.

The Hub Should Build the Network, Not Become the Network

The word hub can lead us toward the wrong mental model.

A conventional service hub looks something like this:

flowchart TD
    Hub --> Person1[Person]
    Hub --> Person2[Person]
    Hub --> Person3[Person]

Everyone comes to the Hub. Information flows through the Hub. Relationships depend on the Hub.

That can be useful during the early stages of a program, but it should not be our definition of mature regional capacity.

A Digital Opportunities Hub should instead help create something more like this:

flowchart LR
    Library --- College
    Library --- Resident
    Library --- Township
    College --- Employer
    Resident --- Employer
    Resident --- Township
    Resident --- Hub
    Township --- Hub
    Hub --- Nonprofit
    Township --- Business
    Business --- Extension
    Nonprofit --- Extension

The distinction is fundamental.

The purpose of the Hub is not to make itself indispensable.

The purpose of the Hub is to make the network more capable.

That means creating relationships that continue after the grant ends, increasing the circulation of knowledge, connecting communities with outside expertise, helping people discover one another, and reducing dependence on any single organization as the source of information or opportunity.

That is capacity building in a much deeper sense.

Strong Communities Need Strong Ties and Bridges

Network theory helps explain why simply creating more connections is not enough.

Dense relationships within a group can support coordination and trust. But communities also benefit from connections spanning otherwise disconnected groups. Ronald Burt’s work describes these gaps as structural holes and distinguishes the value of closure within networks from the value created by brokerage between networks. His empirical work connects brokerage across structural holes with exposure to alternative perspectives, learning, creativity, and the generation of ideas that others judge to be valuable. 2 3

For community development, that means we need both cohesion and bridges.

A farmer connected to a university researcher.

A high school student connected to an engineer.

A township connected to a data scientist.

A small business connected to an artificial-intelligence practitioner.

A library connected to workforce development.

A local technician connected to a manufacturer.

A Tribal community connected to a regional research initiative.

An entrepreneur connected to someone with access to capital.

The question is not whether every participant is connected to everybody else. The question is whether valuable pathways exist across the boundaries that ordinarily separate communities, professions, institutions, and opportunities.

Birds of Unlike Feathers

We often say that birds of a feather flock together. Networks behave that way too. People tend to form relationships within familiar circles: their professions, institutions, communities, industries, and interests.

Those relationships matter. Strong ties create trust, mutual support, and the ability to coordinate. But strong regional networks also need birds of unlike feathers.

I use that phrase to describe useful relationships among people, organizations, disciplines, and communities that would be unlikely to encounter one another through their normal networks.

A farmer meets a university researcher. A student meets an engineer. A township official meets a data scientist. A librarian meets a workforce developer.

The value is not difference for its own sake. It is complementarity across difference.

A connection becomes valuable when someone’s knowledge, capability, experience, resources, or curiosity becomes useful in combination with what someone else brings. An unlikely connection can create possibilities that neither network could easily produce on its own.

Network theory helps explain why. Granovetter’s work on weak ties shows how relationships beyond our closest circles can carry novel information and opportunity. Burt’s work on structural holes explains the value of bridging otherwise separated groups. Birds of Unlike Feathers turns those insights toward a practical community-development question:

Who should know whom, but does not yet?

That shifts our attention from counting participation to discovering missing relationships.

A Digital Opportunities Hub can help those relationships form by understanding what people know, what they need, what problems they are solving, and what resources they can contribute. It can create purposeful connections across sectors, professions, institutions, generations, and communities.

A network can contain tremendous diversity and still be fragmented. What matters is whether useful relationships exist between its different parts.

Difference → Discovery → Complementarity → Connection → Collaboration

The goal is not to make everyone know everyone else. It is to help the region recognize which unlikely connections could matter and create the conditions for those relationships to take root.

Weak Ties Can Carry Opportunity

The idea that connections beyond our closest relationships can provide access to novel information has deep empirical roots.

Mark Granovetter’s landmark 1973 paper, The Strength of Weak Ties, proposed that weak interpersonal ties can act as bridges between otherwise separate social groups, allowing information and opportunities to travel between them. Granovetter explicitly connected this mechanism with information diffusion, mobility opportunities, and community organization. 4

Nearly fifty years later, researchers were able to test that proposition experimentally at an extraordinary scale.

A series of randomized experiments involving more than 20 million LinkedIn users, approximately 2 billion newly formed connections, and 600,000 job transitions provided causal evidence that weak ties can increase job mobility. The effect was not simply “the weaker the better.” The relationship was nonlinear, with moderately weak ties particularly valuable under one measure of tie strength, and the effect also differed across industries. 5

That nuance matters.

The lesson for community development should not be that weak relationships are inherently superior to close relationships.

It is that connections into different networks can carry information and opportunity that may never circulate through someone’s existing network.

Your closest relationships frequently know many of the same people and encounter much of the same information you do. The person one or two networks away may know about the job, technology, funding program, researcher, training opportunity, market, or solution you never knew existed.

A Digital Opportunities Hub can intentionally help create those bridges.

This Changes How We Should Measure Community Development

If we take the network seriously, participation counts become insufficient.

Suppose a Digital Opportunities Hub reports that 500 people attended programs. That tells us something about activity, but relatively little about regional capacity.

A network-oriented evaluation asks different questions.

Did participants gain relationships they did not previously have?

Did those connections cross geography, industry, income, institution, age, or profession?

Did information travel across those relationships?

Did someone discover a career?

Did an organization reuse another organization’s solution?

Did a business discover a technology?

Did a learner encounter an expert?

Did two organizations begin collaborating without requiring the Hub to coordinate them?

Did someone who received knowledge eventually contribute knowledge back?

These are indicators that the network itself is changing.

That matters economically. Research examining 21 billion Facebook friendships found a strong association between economic connectedness, the extent of cross-socioeconomic-status friendship, and upward economic mobility. 6

Importantly, the researchers also found that simply placing people from different socioeconomic groups in the same institutions was not always sufficient: both exposure and the tendency to form relationships conditional on that exposure affected economic connectedness. 7

For Digital Opportunities Hubs, that is a useful warning.

Putting people in the same room is not the same as creating a network.

A more meaningful theory of regional capacity is:

\[\text{Investment} \rightarrow \text{Network Formation} \rightarrow \text{Knowledge Flow} \rightarrow \text{Capability} \rightarrow \text{Opportunity} \rightarrow \text{New Relationships}\]

Those new relationships then become infrastructure for whatever comes next.

The Snowflake Is Really a Network Topology

I have been thinking about the next-generation Digital Opportunities Hub as a snowflake.

At the center is the regional Hub.

Branches extend outward into different dimensions of community development: workforce development, entrepreneurship, health, civic capacity, community data, technology adoption, lifelong learning, and other priorities identified by the region.

One branch might be the Curiosity Library, an all-ages knowledge subscription beginning with a remarkably simple question:

What are you curious about?

The important insight from network science is that those branches should not end at the edge of the snowflake.

Every branch opens into another network.

The Curiosity Library connects:

\[\text{People} \leftrightarrow \text{Interests} \leftrightarrow \text{Resources} \leftrightarrow \text{Courses} \leftrightarrow \text{Experts} \leftrightarrow \text{Organizations} \leftrightarrow \text{Projects} \leftrightarrow \text{Opportunities}\]

Workforce development has another network.

Entrepreneurship has another.

Healthcare has another.

Civic participation has another.

Community data has another.

The Digital Opportunities Hub provides value not simply by maintaining those branches, but by creating bridges between them.

Someone who enters through curiosity might eventually reach workforce development. Someone who enters through a small-business program might discover an artificial-intelligence course. Someone seeking basic digital help might later participate in a citizen-science project. Someone participating in citizen science might become interested in GIS. Someone learning GIS might eventually help a township solve a planning problem.

The snowflake is therefore not an organizational chart.

It is a network topology for community development.

DOIN Can Make the Network Intelligible

This is where the Digital Opportunities Intelligence Network, or DOIN, becomes important.

If the regional Hub helps build the network, DOIN can help us understand it.

Conceptually:

\[\text{Digital Opportunities Hub} = \text{Network Building}\] \[\text{DOIN} = \text{Network Intelligence}\] \[\text{Knowledge Commons} = \text{What Flows Through the Network}\] \[\text{Curiosity Library} = \text{One Way People Enter the Network}\]

DOIN could eventually help communities ask questions that traditional program databases cannot easily answer.

Where are the structural holes in our regional network?

Which organizations bridge otherwise disconnected communities?

Where is expertise concentrated?

Which communities are poorly connected to particular opportunities?

Which resources travel from organization to organization?

Which knowledge gets repeatedly reused?

Where are there highly valuable people, resources, or organizations that almost nobody knows about?

Where has the network become dangerously dependent on a single intermediary?

And most importantly: which kinds of relationships actually lead to useful outcomes?

Those are not simply database questions.

They are questions about how a regional economy and community function.

Not Every Connection Is Equally Valuable

This distinction matters because network development should never become a contest to maximize connections.

For an undirected graph with $N$ nodes and $E$ edges, network density can be expressed as:

\[D = \frac{2E}{N(N-1)}\]

But maximizing $D$ would be a poor community-development strategy. Real networks often contain meaningful community structure, with dense relationships inside modules and fewer connections between them. That structure itself contains information about how the system functions. 1

Other measures may therefore be more useful.

Degree centrality can help identify unusually connected nodes.

Betweenness centrality can help identify important intermediaries.

Community detection and modularity can expose clusters within the regional system.

And identifying structural holes can reveal places where one strategically chosen bridge could expose two communities to information and perspectives that previously remained separated. 1 2

This gives regional development a much richer question than How many people did we serve?

We can begin asking:

How did the structure of opportunity change?

A Good Network Eventually Needs Its Hub Less

There is also a useful way to think about maturity.

At first, almost everything may depend on the Hub:

\[A \rightarrow H \leftarrow B\]

The Hub knows A. The Hub knows B. The Hub makes the introduction.

Later, the Hub begins facilitating direct relationships:

\[A \leftrightarrow H \leftrightarrow B\]

Eventually:

\[A \leftrightarrow B\]

The introduction persists without continued mediation.

As the network matures, participants themselves begin making connections. They create resources. They introduce other people. They mentor. They form projects. They share knowledge. They solve problems together.

The network becomes generative.

That leads to what may be one of the most useful measures of capacity building:

Does the region become progressively less dependent upon the grant-funded Hub to produce valuable interactions?

That is not program failure.

It is institutional success.

A navigator who solves the same problem for 100 people has provided a valuable service.

A navigator who also creates a reusable resource, connects trusted organizations, builds local capability around the problem, and makes it easier for the next 100 people to solve it has begun building infrastructure.

The second model compounds.

The Knowledge Commons Gives the Network Memory

Networks become even more powerful when what moves through them does not disappear after an interaction.

Imagine that one township solves a cybersecurity problem.

Another community adapts the solution.

A library develops public guidance from it.

A college incorporates part of it into training.

A third community improves the resource and contributes the improvement back.

The original interaction has now become a reusable regional asset.

That is the purpose of a knowledge commons.

It gives the network memory.

Instead of repeatedly paying the cost of rediscovering what somebody else already learned, the region accumulates knowledge.

The cycle becomes:

\[\text{Discover} \rightarrow \text{Learn} \rightarrow \text{Apply} \rightarrow \text{Create} \rightarrow \text{Share} \rightarrow \text{Reuse}\]

And reuse creates another discovery event.

Now community development becomes cumulative.

The Most Important Word Is Network

Michigan’s current digital-equity strategy already recognizes that connectivity by itself is insufficient. The state’s definition of digital inclusion includes the tools and resources necessary for people to meaningfully use internet connectivity, while its Digital Equity Plan connects participation with education, healthcare, employment, civic participation, and quality of life. [^2]

MITTEN carries that work into regional communities. Its current regional-resource-hub structure provides a valuable foundation. [^1]

The next opportunity is to take the final word in MITTEN more seriously.

We should continue helping people overcome digital barriers.

But we should also connect them with learning, people, knowledge, institutions, tools, careers, businesses, projects, and opportunities.

We should identify the parts of our communities that remain disconnected from one another.

We should intentionally create bridges.

We should build regional knowledge commons so that solutions can travel.

We should measure whether knowledge circulates and whether relationships produce meaningful outcomes.

And we should design Digital Opportunities Hubs whose long-term success is measured not only by how many services they provide, but by how much stronger, more connected, and more generative the surrounding regional network becomes.

That returns us to the word that has been there from the beginning.

Network.

Perhaps the next generation of MITTEN does not require abandoning what Michigan built.

Perhaps it requires taking the name more seriously.

Physical networks move bits.

Human networks move trust.

Knowledge networks move understanding.

Economic networks move opportunity.

The next generation of digital opportunity should help Michigan’s regions learn how to connect all four.

References

https://www.michigan.gov/leo/news/2025/02/28/mihi-awards-10m-to-13-organizations-across-michigan-to-improve-digital-access-statewide.

https://www.michigan.gov/leo/bureaus-agencies/mihi/michigan-digital-inclusion-resources.

A Note on Evidence and Provenance

The citations in this op-ed are intentionally attached to the claims they support.

MIHI’s documentation establishes the purpose and current structure of MITTEN and Michigan’s broader digital-inclusion strategy. Granovetter provides the theoretical foundation for weak ties; Burt for structural holes, brokerage, and network closure; Newman for community structure and modularity; the Science weak-ties experiment provides large-scale causal evidence connecting network structure with job mobility; and the Nature economic-connectedness studies provide evidence connecting cross-class social relationships with economic mobility.

Just as importantly, the Curiosity Library, DOIN, snowflake model, knowledge commons, and proposed next-generation Digital Opportunities Hub are not presented as findings from that literature. They are the original synthesis advanced in this op-ed.

The provenance is therefore deliberately layered:

Established research explains how networks behave. Michigan’s documentation establishes the policy and program context. The Digital Opportunities Hub, DOIN, Curiosity Library, snowflake topology, and knowledge commons are the proposed regional-development model built from those foundations.

That distinction matters because the central contribution of the piece is not simply the observation that networks matter. It is the argument that network science provides a practical design language for the next generation of digital-opportunity infrastructure in Michigan.

What changed

  • Newman: narrowed the modularity sentence so the citation supports precisely what the prose claims.
  • Chetty et al.: removed the unnecessary “privacy-protected” characterization and made the definition of economic connectedness more precise.
  • Provenance note: replaced the repetitive source-by-source explanation with a three-layer distinction between established research, Michigan program context, and your original synthesis.
  • Attribution: DOIN, the Curiosity Library, snowflake topology, knowledge commons, and next-generation Hub remain clearly yours rather than being inadvertently attributed to Granovetter, Burt, Newman, Chetty, or MIHI.
  • Core argument: unchanged. The central claim remains that Michigan should treat the “Network” in MITTEN as a design principle rather than simply part of the program name.

  1. Newman, M. E. J. “Modularity and Community Structure in Networks.” Proceedings of the National Academy of Sciences 103, no. 23 (2006): 8577–8582. https://doi.org/10.1073/pnas.0601602103. ↩ ↩2 ↩3

  2. Burt, Ronald S. “Structural Holes versus Network Closure as Social Capital.” In Social Capital: Theory and Research, edited by Nan Lin, Karen Cook, and Ronald S. Burt. Aldine de Gruyter, 2001. ↩ ↩2

  3. Burt, Ronald S. “Structural Holes and Good Ideas.” American Journal of Sociology 110, no. 2 (2004): 349–399. ↩

  4. Granovetter, Mark S. “The Strength of Weak Ties.” American Journal of Sociology 78, no. 6 (1973): 1360–1380. ↩

  5. Rajkumar, Karthik, Guillaume Saint-Jacques, Iavor Bojinov, Erik Brynjolfsson, and Sinan Aral. “A Causal Test of the Strength of Weak Ties.” Science 377, no. 6612 (2022): 1304–1310. https://doi.org/10.1126/science.abl4476. ↩

  6. Chetty, Raj, et al. “Social Capital I: Measurement and Associations with Economic Mobility.” Nature 608 (2022): 108–121. ↩

  7. Chetty, Raj, et al. “Social Capital II: Determinants of Economic Connectedness.” Nature 608 (2022): 122–134. https://doi.org/10.1038/s41586-022-04997-3. ↩