Extractive vs. Generative Ownership of Telecom Infrastructure

In her 2012 book Owning Our Future: The Emerging Ownership Revolution, Marjorie Kelly, Executive Vice President and a Senior Fellow with The Democracy Collaborative, provides a framework for understanding and distinguishing what she describes as “generative” vs. “extractive” ownership designs. In key respects, the book builds on Kelly’s first book, The Divine Right of Capital: Dethroning the Corporate Aristocracy, published more than a decade ago (you can read the latter’s introduction here).

Drawing an apt and powerful parallel to the divine right of kings, Kelly’s first book does a masterful job of opening readers’ minds to the arbitrary and distorting nature of the ownership and control model embodied in today’s publicly-traded corporations. In Owning our Future, she does an equally impressive job helping readers understand and appreciate the significance of the range of alternative ownership structures emerging across the economy. A clear, succinct and enjoyable read, Owning Our Future clarifies:

the core underlying components that comprise “a family of generative ownership designs;”
how the expansion of “generative” ownership can help address the growing problems associated with the overly-financialized and “extractive” model of capitalism that remains dominant today, including acute and chronic economic problems such as the the 2008 financial crisis and its still-unresolved aftermath, as well as planetary-scale environmental problems like global warming.

In a May 17, 2012 talk entitled From the Fringe to the Leading Edge: Generative Design Goes to Scale, at the annual conference of the Business Alliance for Local Living Economies (BALLE), Kelly highlighted the fundamental importance of ownership in our economy and our world, and the problems caused by today’s dominant form of ownership:

Every economy is built on the foundation of ownership… Questions about who owns the wealth-producing infrastructure of an economy, whose interests it serves, these are among the largest issues any society can face…The crises we face today, ecologically and financially, are tangled at their root with the particular form of ownership that dominates our world – the publicly traded corporation, where ownership shares trade in public stock markets. The revenues of the 1,000 largest of these corporations represents roughly 80% of global GDP.

Kelly then briefly reviewed what her years of research have led her to understand about “generative” alternatives to the dominant “extractive” form of ownership. “The first and most important difference” she says is a “Living Purpose.”

…the many ownership alternatives – from community land trusts and cooperatives to social enterprises and community ownership of the commons – these alternatives represent a single, coherent school of design. It’s a family of generative ownership designs. Together, they form the foundation of a generative economy.

Generative means the carrying on of life, and generative design is about the institutional framework for doing so. In their basic purpose, and in their living impact, these designs have an aim of generating the conditions where all life can thrive. They are built around a Living Purpose.

This is in contrast to the dominant ownership designs of today, which we might call extractive. Their aim is maximum extraction of financial wealth. They are built around a single-minded Financial Purpose.

But, according to Kelly, “purpose alone isn’t enough.” Also needed, she says, is “the presence of at least one other structural element that holds that purpose in place.” These additional elements of generative design are:

Membership. Who’s part of the enterprise? Who has a right to a say in profits, and who takes the risk of ownership? Corporations today have Absentee Ownership. Generative ownership has Rooted Membership, with ownership held in human hands.

Governance. Extractive ownership involves Governance by Markets, where control is linked to share price. Generative ownership involves Mission-Controlled Governance, with control held in mission-oriented hands.

Finance. Instead of the Casino Finance of traditional stock market ownership, generative approaches involve Stakeholder Finance, where capital becomes a long-term friend.

Networks…If traditional approaches use Commodity Networks, where goods trade based solely on price, generative economies use Ethical Networks, which offer collective support for social and ecological norms.

Kelly then notes that, while “[n]ot every ownership model has every one of these design elements…the more elements that are used, the more effective the design.”

How does this apply to the telecom sector?

Having listened to many an earnings call and followed the telecom industry for nearly three decades, it seems pretty clear to me that the dominant publicly-traded cable and telephone companies have an overriding Financial Purpose, as expressed by management’s intense focus on cash flow, stock price, profits, market share, average revenue per unit, pricing power, and other financial metrics.

Related to these metrics is an intense focus (in statements made to Wall Street analysts as well as actual financial decision-making) on “return of capital to shareholders,” largely in the form of dividends and stock buybacks.

While this is perfectly legal and very understandable from the perspective of corporate management (whose compensation is often based on stock price), the fact is that these returns to shareholders are allocations of cash flow that might otherwise be used to deliver more value to customers. For example, this cash flow could be invested in network upgrades and/or improved customer service. The latter is particularly notable, since both the cable and telephone industries have longstanding and well-earned reputations for poor customer service, as reflected in virtually all national surveys (and plenty of anecdotes shared among friends and posted on the web). This, I believe, is largely because, as monopolists or duopolists with substantial market power and extractive ownership designs, these companies tend to be more focused on satisfying the desires of shareholders and Wall Street analysts than those of largely-captive customers with limited options for taking their business elsewhere.

These same industry dynamics are also clear evidence that, in addition to Financial Purpose, the nation’s large publicly-traded cable and telecom giants are also characterized by what Kelly refers to as Absentee Ownership, Governance by Markets, Casino Finance and Commodity Networks, and that their managements are heavily influenced by pressure from Wall Street analysts and traders, whose work takes place even more deeply at the core of our economy’s financial extraction machinery.

AT&T as an example of extractive ownership

In my view, AT&T, the nation’s largest ILEC, is a good example of the kind of financially extractive ownership model that currently dominates the top tier of telecom companies, virtually all of which have their historic roots in a monopoly or near-monopoly market environments. Below is a brief review of key elements of the company’s history over the past decade or so, to illustrate what I mean.

In 2004 AT&T (then SBC Communications) announced that its next-generation network upgrade strategy would rely mainly on fiber-to-the-node (FTTN) technology, which uses a form of DSL technology to deliver both Internet and TV services over the final stretch of copper wires that connect customer locations. The initial budget allocated $6 billion to deploy a FTTN network (dubbed U-verse) that passed 18 million premises.

By late 2012, AT&T’s U-verse footprint had expanded to 24.5 million premises, which suggests a total U-verse investment up to that point of about $8 billion. At that time, AT&T announced Project Velocity IP (VIP), which was to invest another $6 billion over three years to expand U-verse availability to 33 million premises (roughly 43% of its total footprint), while deploying next-generation DSL technology to boost Internet speeds for another 24 million premises, suggesting a total next-generation wireline investment of roughly $14 billion over the course of a decade.

It’s important to note that, based on AT&T’s announced plan, when this second major upgrade program was to be completed, roughly 19 million premises (one of every four passed by its networks) would not have access to ANY wireline broadband service from AT&T.

To put AT&T’s network upgrade strategy in a financial and corporate strategy context, consider that, between 2006 and 2015, AT&T returned an average of nearly $14 billion per year to its shareholders in the form of dividends and stock buybacks. This means the company has returned roughly as much money to shareholders in an average year as it has allocated over a decade to its next-generation wireline network upgrade. In total, between 2000 and 2015 the company returned nearly $172 billion to shareholders in the form of dividends and stock buybacks. That’s equal to 73% of its total capital spending during this period, with two years, 2012 and 2013, seeing shareholder returns exceed CapEx (117% of CapEx in 2012 and 107% in 2013). By my estimation, if AT&T had reallocated just half of these shareholder returns to full “fiber-to-the-premise” network upgrades, it could have extended state-of-the-art all-fiber networks to nearly 90% of the roughly 76 million premises passed by its network, assuming construction costs comparable to those budgeted by Verizon, the nation’s second largest telco, nearly a decade ago. Boost that CapEx reallocation percentage a bit more, and virtually all of AT&T’s customers and the communities in which they live and work would by now be enjoying the direct and spillover benefits enabled by fiber’s symmetrical gigabit-level speeds and superior reliability.

A related indicator of AT&T’s priorities is its 2015 acquisition of DirecTV for $67 billion, about $48.5 billion of which was financed by equity and the remainder by debt. While this may prove to be a smart move for AT&T from a competitive and financial perspective, given the competitive weakness of its underfunded but once much-touted U-verse upgrade strategy, it’s worth noting that this massive M&A investment: 1) generated virtually no new infrastructure or competitive entry; 2) involved an additional debt burden greater than the total amount AT&T had invested in the initial U-verse and follow-on Project VIP phases of its wireline network upgrade, and a total acquisition-related investment nearly five times the financial magnitude of these wireline upgrade investments.

One need not be a technology or financial expert to get a sense from the above that the strategic priorities driving AT&T’s investment decisions focus more on share price and profits than on maximizing the social value of the Internet’s “spillover rich” infrastructure within the service territory originally granted to Ma Bell as a protected monopoly, and later inherited (and largely reconsolidated) by the corporate entity we now know as AT&T. While this strategy may make very good sense from the perspective of AT&T’s management and shareholders, my point here is that, given the company’s (and its peer group’s) dominant role in the communication sector and our national political economy, “what’s good for AT&T,” may not be so good for the nation as a whole. And, if that’s the case, perhaps there’s more that we, as a society, can and should do to shift the focus of public policy toward an approach to the Internet that does, in fact, focus on maximizing its positive (yet difficult to quantify and even more difficult to internally monetize) direct and indirect spillover effects.

In the next post in this series I consider Kelly’s framework in the context of the local broadband access market.

Primary takeaways

Digital inequality shows larger impacts on youth academic performance as compared to time spent on screens.
Digital skills play a significant role in mediating unstructured online engagement (social media use, playing video games, browsing the web) and youth academic, social, and psychosocial development.
Unstructured online engagement and face-to-face social interaction are complementary and continuously interact to create and enhance youth capital outcomes.

A familiar story: concerns of screen time

Today’s discussions of adolescent well-being have coalesced around a clear narrative: teenagers spend too much time online, and their academic performance, mental health, and social lives are deteriorating as a result. A steady stream of academic papers, books, and op-eds, alongside a growing number of policy proposals––school phone bans, age-gated social media use, restrictive screen-time limits––rest on the same underlying claim, aligning with a contemporary, digitized version of the displacement hypothesis:

Screen time, particularly the unstructured, free-time spent on social media, gaming, watching video content, or browsing the web, is said to displace the productive face-to-face activities that build adolescents into capable adults.

The implied and often practiced solution is restriction. In response, this dissertation tested this claim directly, and placed it within the broader context of adolescence.

Across three years, I followed 653 Michigan adolescents from early through late adolescence: in grades 8 or 9 (survey one, 2019) to grades 11 or 12 (survey two, 2022). Notably, these students, studied over time, were part of a broader pooled sample of 5,825 students across the same eighteen highschools. The study window captured the year before and the year after the peak of the COVID-19 pandemic and related lockdown orders, functioning as an unprecedented stress test for theories of adolescent social, academic, and digital life and, importantly, as a benchmark to compare the effects of pandemic-related change and inequality to those effects from screen time alone.

Across four studies of adolescents, consisting of six cross-sectional and longitudinal analyses, findings are not consistent with the displacement narrative, nor the broader concerns about the time youth spend on screens.

Findings are, however, consistent with something the current public and (most) academic discussions have largely overlooked or ignored: the gaps and inequalities that determine whether adolescents can access and use the internet meaningfully in the first place.

What the displacement hypothesis overlooks

Displacement and related research and policy concerning the time young people spend online assumes a “zero-sum” model of adolescent day-to-day time. An hour online is an hour not spent studying, reading, sleeping, or interacting face-to-face (i.e., time spent on more productive or developmentally “better” activity).

Indeed, this makes sense logically. However, as an empirical claim, this model requires time spent online to behave differently from all other ways adolescents allocate time; it must produce uniquely negative outcomes and be inherently harmful across digital contexts, rather than the typical mix of trade-offs corresponding to, and often overlooked among any other social or developmental context.

Yet, online time does not differ from other youth activity. Instead, I find it has a mix of pros, cons, and even some “uniquely digital” benefits which youth utilize for social and academic gains. When I compared unstructured digital media use against traditional face-to-face interaction and activities, both produced similar patterns: some negative associations with academic outcomes, some null, and some positive.

Trade-offs within traditional face-to-face activity (for example, social time with friends and family, or time spent in after-school extracurriculars) are treated as ordinary developmental experiences that must be experienced for the betterment of development. The identical trade-offs involving digital time tend to be overlooked or ignored, and online engagement is perceived as altogether harmful.

A growing body of evidence, including this dissertation, do not support that distinction. Indeed, the developmental context is routinely misread, leaving out the context of the experiences and time spent on digital, as well as face-to-face activities, interactions, existing inequalities, and changes inherent to development. As such, I proposed a novel framework to understand these contexts:

Digital capital exchange

Rather than treating screen time as a unified harm, this dissertation advances an “exchange”-based framework, grounded in James Coleman’s theories of youth capital and digital inequality scholarship, particularly following Eszter Hargittai, Jan van Dijk, and Alexander van Deursen (see this list of all dissertation references for full works).

The core proposition is that adolescents’ online engagement is not an alternative to developmental activity but another, albiet modern domain through which young people accumulate and mobilize online resources––particularly digital skills––that work alongside existing social networks and experiences to be exchanged for human capital (measured as: academic achievement, aspirations, STEM interest) and social capital (peer networks, community participation, extracurricular involvement).

Online time is not the mechanism; instead, it is digital skills that I find to be the most vital component in youth capital exchange and enhancement. Unstructured online engagement contributes to online skills; those skills, accumulated and mobilized alongside existing peer, family, and community networks, translate into the outcomes researchers and parents care about, i.e., academic achievement, aspirations, and face-to-face interaction and social networks.

This digital capital framework treats online and in-person contexts as complementary rather than antagonistic, and it situates adolescents’ digital lives within the structural conditions––connectivity quality, device reliability, autonomy of use––that determine whether exchange can occur at all.

Methods (in brief)

Paper-and-pencil surveys were administered to students in classrooms at two time-points: spring 2019 (N=2,876) and spring 2022 (N=2,949), across the same eighteen predominantly rural Michigan schools, grades 8–12. Official, nationally-ranked standardized reading, writing, and math test scores (PSAT 8/9, PSAT 10, SAT; College Board) were then anonymously linked to students’ survey responses with the help of participating districts.

Cross-sectional path analyses modeled pooled and wave-specific samples (pooled N=5,825); two-wave cross-lagged panel models tested reciprocal, longitudinal relationships on the 653 students who completed both surveys. Multi-group analyses of the cross-lagged panel models compared relationships between girls (N=345) and boys (N=308). All longitudinal models included time-invariant socioeconomic covariates as well as time-varying covariates to reduce omitted-variable bias.

Key findings: an overview

To summarize, to the best of my ability, eight chapters across 376 pages, I present two primary findings:

First: digital inequality predicted larger and more consistent declines in human capital than screen time did.

Unreliable home internet and technology maintenance problems––experiencing and/or dealing with broken or outdated devices and software, restrictive school-issued hardware, issues with connecting to or maintaining internet access––decreased youth GPA and standardized test achievement. And, these effect sizes were substantially larger than any negative direct effect from unstructured digital media use.

Across all four empirical studies, digital inequality emerged as the most substantial predictor of academic and developmental decline.

Second: digital skills mediated the relationship between online time and adolescent academic and social outcomes.

Unstructured digital media use, particularly online gaming and web browsing, predicted higher internet and social media skills for adolescents, which in turn predicted stronger academic achievement and self-efficacy (human capital), and social interaction and extracurricular participation (social capital). The positive indirect effect of screen time through skills offset or exceeded any small negative direct effects across several outcomes (supporting our existing peer-reviewed work: Hales & Hampton, 2025, and which you can read more about here).

These exchange processes were amplified when peer and family networks were modeled alongside digital skills, consistent with the premise that online and offline contexts operate together rather than in competition. The effect was not universal: social media skills amplified rather than offset a negative association with consistency of interest, one of the two subscales of grit. The exchange framework describes a contextual and conditional, domain-specific mechanism, not a blanket defense of time spent online.

Implications

If digital inequality, and not screen time, is the primary predictor of adolescent academic and developmental decline, and still warrants concern regarding access quality and experience even with the broader adoption of digital devices across the United States, the current policy emphasis on restriction is pointed at the wrong target. The evidence supports a different set of priorities.

Stable, reliable home (fast) broadband should be treated as an educational prerequisite rather than a consumer amenity. Unreliable connectivity exerted larger downward pressure on human capital than any measure of screen time, and that pressure intensified during the pandemic-era reliance on digital infrastructure. Technology maintenance, device repair, replacement, technical support, and the flexibility to install software and explore the web autonomously, matters as much as initial access, and school-issued devices that restrict autonomous use appear to hinder skill accumulation rather than support it.

Restrictive parental mediation of internet use was negatively associated with grit and self-efficacy at magnitudes comparable to the positive contributions of face-to-face activity. This challenges the assumption that digital restriction functions protectively. Instructive mediation, teaching adolescents to verify information, navigate platforms critically, and mobilize online resources toward meaningful ends, is the posture the data supports.

Finally, the technical skill-building that occurs through gaming, self-directed exploration, and deep web use is skill-building, not wasted time. Closing the persistent gender gap in these domains likely requires legitimizing technical play for girls, rather than restricting it for everyone.

None of the above is an argument that screen time is benign. It is an argument that screen time is the wrong focus, particularly when studied mostly in isolation. Context matters substantially, whether that is time spent on other activities during adolescence, the period of adolescence itself, digital inequality, resources gained from such online use, and how all such factors interact. The factor that predicts whether a given adolescent can convert online engagement into capital outcomes is structural: access, infrastructure, skills, and the autonomy to use them. These factors are distributed unevenly, and its uneven distribution, not hours logged, is what separates adolescents who thrive from those who fall behind.

The full dissertation is available through Michigan State University’s ProQuest archive, or see the embedded full-text PDF below. I’m happy to share papers, preprints, or the underlying framework with anyone interested and working in this area––don’t hesitate to reach out via my contact form. Thanks for reading.

Tags: corporate finance ownership models policy public infrastructure

Extractive vs. Generative Ownership of Telecom Infrastructure