Resource Distribution and Power Dynamics in Decentralized Networks

Introduction

The idealized vision of decentralized coordination triggered by the invention of Bitcoin continues to attract entrepreneurial and general interest. But while cryptonetwork innovators are obviously onto something unique and interesting, these emerging social systems are far from immune to problems that have plagued human institutions historically.

One way to conceptualize decentralized networks in terms of resource distribution, power dynamics, and governance is to think of these systems as fields. This post explains the meaning of this concept in sociology and how it could be operationalized when analyzing cryptonetworks. A realistic analytical framework for thinking about power and resource distribution early on will hopefully assist in reducing the likelihood of these systems reproducing or even amplifying the various imbalances that characterize the economy as we know it today.

What is a field?

In sociology, the term field denotes a structured social and symbolic setting in which individuals and groups acquire positions and act, and in which systems of meaning, institutions and hierarchies are formed, maintained and challenged.

As arenas of production, circulation and accumulation of goods, services, knowledge and status, the structure of a particular field is determined by the distribution of field-specific resources and, by extension, relations among its constituents.

As individuals and groups cooperate, compete and strategize, they either reinforce or challenge that structure. Under normal circumstances, the participants in a field accept the fundamental rules of the game. Indeed, this acceptance generally serves as a precondition for legitimately entering the field in the first place. But occasionally, these rules — and the power to define them — become actively contested stakes within the field.

Fields are not neutral, open and free marketplaces. At any given time, there are norms, limitations, inertia, and other structural forces that make certain development trajectories — for individuals, groups, and the field as a whole — more likely than others. As a result, the reality of a field is not fully reducible to the individual properties of its constituents, but should be analyzed in terms of the structural relations that constitute the field as a whole.

The boundaries of a field are not always clear or fixed and the concept can be applied at various levels of analysis. Consequently, many different and overlapping fields can be identified, from very large social universes such as science, business or art, to much more specialized arenas such as climate research, US retail business, or contemporary Italian painting, to even more narrowly defined microcosms such as a particular network of researchers, a local consumer electronics retail market, or a community of art professionals in a particular city.

Decentralized networks can also be thought of as fields that are emerging to compete within broader, incumbent-dominated fields in various areas of economic activity. Approaching cryptonetworks from such a perspective is analytically useful because most fields are characterized by similar properties and tendencies. For example:

  • Fields initially form when a large enough group is able to establish a local social order (a game worthy of playing, so to speak), potentially to compete within an existing field.
  • Competition and cooperation over field-specific resources, including the power to legitimately define and impose the fundamental rules of the game.
  • Unequal distribution of these resources and, as a result, structuring into dominant and subordinate positions. This does not preclude a field from having a relatively egalitarian power structure.
  • Tendency of the dominant positions to struggle for consolidation and conservation, and subordinate positions for disruption and change. Large structural shifts become possible as existing rules and arrangements break down, often in the context of some sort of crisis, allowing the structure and culture of the field to be redefined through individual and collective agency.
  • Tendency of the dominant groups to justify the reality and effects of unequal resource and power distribution, often relying on a set of fundamental beliefs and assumptions about humans and society.
  • Relative position in the field has an impact on individual predispositions, although the full meaning and effect of this is not necessarily acknowledged or understood by the participants themselves.
  • Tendency to have economically and culturally dominant poles as discrete resources accumulate in the hands of different constituents. This leads certain groups to fight for goals and values that go beyond strictly individual or financial self-interest (often relying on notions such as “fairness” or “public purpose”).

Various iterations of field theory include additional avenues for analysis (there’s a list of further reading material for anyone interested below), but these are sufficient to raise the following question: what would basic field analysis consist of when applied to decentralized networks?

Field analysis for decentralized networks

In the first approximation, such an exercise would include the following steps, together with some inferences based on the standard formulation of the theory (from here on, the words “network” and “field” are used interchangeably):

(1) Understanding the formal rules of engagement as defined by the protocol and its governance system.

  • Defining the rules of communication and governance has important implications for resource and power distribution in the future development of the network.
  • For example, initial and ongoing funding mechanisms for developers and transaction validators have a direct effect on the evolving structure of the field, the key question being: how are resources initially allocated and how can they be used or accumulated over time?

(2) Identifying network participants and stakeholders.

  • In-depth analysis would include studying the history of key individuals, groups and institutions, their production of shared ideologies — especially the dominant one — and how these influence decision-making and action.
  • For example, network constituents could include founding entrepreneurs, core developers, managing company, not-for-profit foundations, various supply- and demand-side actors (miners, users, etc.), investors, speculators, exchanges, companies using or building on the network, regulators, etc.
  • Understanding the harmony (or lack thereof) between the experienced reality of the field and subjective values of the individuals and groups involved. This can help in projecting future growth and challenges, especially as openness to cooperation and new people and ideas becomes an important driver of mass adoption. Note that the average participant may remain oblivious to the underlying power struggles within the field, participating happily in any network that delivers the service desired in the best possible way.
  • Government and policymakers, by introducing regulatory clarity and safeguards for different participants (which often amount to barriers of entry), play a key role in creating fields that are relatively stable.

(3) Identifying the resources at stake.

  • This could include formal decision-making power (both on- and off-chain); political capital of founders, core developers, and other community members; technical talent; reputation; mining/staking power; effective control over financial resources; general economic and social capital; anything related to the ability to fork the network; etc.
  • The most highly valued resource does not have to be financial, although it often becomes a defining aspect of the field’s power structure.

(4) Understanding the historical and current distribution of these resources, including the distribution at network launch and stock/flow dynamics enabled and amplified by the rules of the protocol.

  • Organized and increasingly institutionalized competition over network-specific resources is likely to become a defining feature of large decentralized networks.
  • Consolidation tends to benefit the dominant groups, i.e. those who already control a lot of resources.
  • Extreme inequality in resource and power distribution leads to conflict and resistance. In a worst case scenario, this results in disintegration, especially if near-substitutes for the services provided are readily available. This can be avoided if users prioritize quality of service over egalitarian values — the “paradox” of preferring good governance to democratic governance, or accepting high levels of inequality in exchange for some good/service perceived as “worth it”.
  • For example, networks where the majority of participants are passive (but satisfied) consumers may be more accommodating to extreme power imbalances and, by extension, more traditional forms of (centralized) governance, whether formalized or not.
  • Differentiating between networks driven by ideology vs. pragmatism. The former are more likely to collapse under the weight of their own ideas, while the latter are more likely to reproduce the familiar problems of power/resource inequality, although potentially in a form that many are willing to tolerate, either out of convenience, necessity, apathy, or all three combined (as is often the case with existing economic and political systems).
  • Assuming that at least some networks will become globally important, time will tell how easy it will be to steer their development, or fork/launch networks with an actual chance to catch up and compete.

(5) Identifying competitive and cooperative drivers, ongoing conflicts and alliances.

  • Group interests combined with growing complexity lead to increasing levels of organization and institutionalization, allowing for more powerful forms of both maintaining and challenging the structure of the field.
  • As a network grows in importance and value, it naturally becomes increasingly attractive for hackers or other groups to attack or misuse it.

(6) Detailed understanding of governance mechanisms.

  • Differentiating between on- and off-chain governance, defined as any design feature or control mechanism that steers the system through its various stages of development. This includes the introduction of checks and balances, various trade-offs between speed/efficiency and broad participation, dispute resolution mechanisms, as well as links to existing systems of law and governance.
  • For example, traditional forms of corporate governance; “benevolent dictatorship” (charismatic founder or core developer); technocracy (rule of technologists); plutocracy (governance rights connected to coin/token holdings); possibly also more experimental systems such as holacracy (off-chain), liquid democracy (on-chain), futarchy (use of prediction markets to pick policies that are expected to deliver on collectively agreed upon performance metrics); quadratic voting (each additional vote becomes increasingly expensive to the voter), etc.
  • Networks with higher stakeholder engagement and a more broadly distributed sense of ownership may require much more distributed, participatory and democratically legitimized governance systems to avoid conflict. This can be mediated through various decentralized governance platforms and interfaces.

Again, more sophisticated iterations of field theory offer additional angles, especially in relation to decision-making and action, but the steps above represent a starting point for describing a particular network or DAO as a field. An important benefit of a field-theoretic perspective is that it lends itself easily to both historical and comparative studies on how different networks evolve and are governed. As decentralized networks grow and mature, such comparative research may become increasingly relevant and insightful.

Conclusion

As long as we’re dealing with human beings, the age old struggle to accumulate power and other resources is likely to remain part of the picture. Time will tell whether the unique characteristics of decentralized networks, as compared to more traditional forms of organization, are sufficient to avoid a tendency towards concentration. Field theory, as a general theory of local social orders, can be applied to frame and analyze these dynamics — a precondition for addressing their more negative long-term consequences.

Further reading on field theory

Field theory has been developed with varying points of emphasis in different social scientific disciplines. Below is a list of references — some of which were used as source material for this post — for anyone interested to learn more.

  • General overview: Martin, J. L. (2003). What is Field Theory? American Journal of Sociology, Vol. 109, No. 1, pp. 1–49.
  • Early social-psychological perspective: Lewin, K. (1951). Field theory in social science. New York: Harper.
  • Organizational theory perspective: DiMaggio, P. & Powell, W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, Vol. 48, No. 2, pp. 147–160.
  • Social skill and action perspective: Fligstein, N. (2001). Social Skill and the Theory of Fields. Sociological Theory, Vol. 19, No. 2, pp. 105–125.
  • Stratification and power struggles perspective: Hilgers, M. & Mangez, E. (2015). Bourdieu’s Theory of Social Fields: Concepts and Applications. London and New York: Routledge.

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