Resource Distribution and Power Dynamics in Decentralized Networks

Introduction

The idealized vision of decentralization inspired by the invention of public blockchains continues to attract entrepreneurial and general interest. But while proponents are obviously onto something interesting, these emerging social systems are far from immune to problems that have plagued human institutions historically.

One way to conceptualize blockchain 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 can be operationalized when analyzing cryptonetworks. A realistic analytical framework for thinking about power and resource distribution early on will hopefully reduce the likelihood of these systems reproducing — or even amplifying — the various imbalances that characterize the digital 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 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 compete and cooperate, they either reinforce or challenge the field’s structure. Under normal circumstances, the participants accept the fundamental rules and regulations of the field. Indeed, this acceptance generally serves as a precondition for legitimately entering the field in the first place. But occasionally, these rules themselves — and the power to define them — become an object of active contention.

Fields are never entirely neutral and open marketplaces. At any given time, there are power relations, norms, institutional inertias, and other structural forces that make certain actions and development trajectories — for individuals, groups, and the field as a whole — more feasible than others. As a result, the reality of a field is not reducible to the individual actions and preferences 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 market, or a community of art professionals in a particular city.

Blockchain industry as a whole can also be thought of as a field, while individual networks can be analyzed either as semi-autonomous sub-fields, or as competitors in broader, incumbent-dominated fields. Framing blockchain networks as fields is analytically useful because most fields share a number of similar properties and tendencies. For example:

  • Fields initially form when a large enough group establishes a ‘local social order’ by identifying the key resources at stake (a game worthy of playing), 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 that the participants in the field are expected to follow.
  • Unequal distribution of said resources and, as a result, structuring into dominant and subordinate positions (although this does not preclude a field from having a relatively egalitarian power structure).
  • Tendency of the dominant players to struggle for consolidation/conservation, and subordinate players for disruption/change. Large structural shifts become possible as existing rules and arrangements break down, often in the context of a 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 unequal distribution of power/resources and its effects, usually relying on a set of fundamental beliefs and assumptions about humans and society.
  • Relative position in the field has an impact on individual predispositions (views, opinions, behavior), although the full meaning and effect of this is not necessarily acknowledged or understood by each individual participant.
  • Tendency to have economically and culturally dominant poles as discrete resources (expertise, capital, status, etc.) accumulate in the hands of different constituents. This usually leads some groups to actively promote goals and values that go beyond strictly individual and/or financial self-interest (often relying on notions such as ‘fairness’, ‘public purpose’, or ‘common good’).

Different iterations of field theory include additional aspects (there’s a list of further reading material for anyone interested at the end of this post), but the list above is sufficient to raise the following question: what would basic field analysis consist of when applied to blockchain networks?

Blockchain networks as fields

In the first approximation, such an exercise would include the following steps (from here on, the words ‘network’ and ‘field’ are used interchangeably):

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

  • Establishing a protocol and defining the rules of governance determines not only the initial resource and power distribution but also the more/less likely future trajectories for various participants.
  • 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.

  • Detailed analysis would include studying the history of key individuals, groups and institutions, the nature and basis of shared ideology, and how these influence decision-making and action.
  • For example, network constituents may include founding entrepreneurs, core developers, private companies operating and maintaining the networks, not-for-profit foundations, end-users of the services provided by the network, investors, financial 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/views of the individuals and groups involved. This can help in projecting future growth and challenges, especially as openness to cooperation and new people or ideas becomes an important driver of mass adoption. Note that the average user of the network may remain oblivious to the underlying ideological or power struggles within the field, participating happily in any network that delivers the service desired in an easy-to-use 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; control over financial resources and other forms of economic, social, or technological capital; ability to fork the network; etc.
  • The most highly valued resource does not have to be financial, although financial capital usually becomes a defining aspect of the field’s power structure.

(4) Understanding the historical and current distribution of the field’s resources, including their distribution at network launch and stock/flow dynamics enabled by the rules of the protocol and its governance.

  • 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 (if not entirely, then at least in terms of broad support/adoption), while the latter are more likely to reproduce the familiar structure and problems of existing institutions, which many may be willing to tolerate out of convenience, necessity, apathy, or all three combined (as is often the case with existing institutions).

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

  • Group interests combined with growing complexity lead to increasing levels of institutionalization, allowing for more powerful forms of maintaining the existing structure of the field.
  • As a network grows in importance, value, or adoption, it naturally becomes increasingly attractive to malicious actors.

(6) Detailed understanding of governance mechanisms.

  • Differentiating between on- and off-chain governance, defined as any design feature or control mechanism that maintains and steers the system. 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 law and institutions.
  • 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 liquid democracy (on-chain), futarchy (use of prediction markets to pick policies that are expected to deliver on collectively agreed upon performance metrics), and quadratic voting (each additional vote becomes increasingly expensive to the voter).
  • Networks with higher stakeholder engagement and a more broadly distributed sense of ownership may require more distributed, participatory and democratically legitimized governance systems to avoid conflict. This can be mediated through various decentralized governance platforms/interfaces and the existing legal system.

Again, more sophisticated iterations of field theory offer additional angles, especially in relation to decision-making and action, but the steps above are sufficient for analyzing a particular blockchain network 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 will become increasingly helpful in designing the most socially beneficial networks and governance systems.

Conclusion

One of the most important determinant of social structure in any field of human activity is the distribution of power and economic resources. Time will tell whether the unique characteristics of public blockchain networks, as compared to more traditional forms of organization, are sufficient to avoid the age-old tendency towards concentration. Field theory, as a general theory of local social orders, can be used to frame and analyze these dynamics, ideally resulting in more thoughtful network design and governance.

Further reading on field theory

Below is a list of references — some of which were used as source material for this post — for anyone interested to learn more about field theory.

  • 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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