Platforms and Cultural Production — David Nieborg and Brooke Erin Duffy

David Nieborg and Brooke Erin Duffy · 2022

Summary

The central question: what are the political, economic, cultural and social results when cultural production becomes platform dependent? “Cultural production” here is narrow on purpose. It means market-based making of symbolic goods (news, games, social media content) by organisations or by individual creators. It does not mean everyday users. The platforms in focus are the ones at the heart of media, such as Google, Apple, Meta and the big Chinese firms. Airbnb and Uber are out of scope.

The thesis. Platforms and online communication come with a story of democratisation: it is easier than ever to make and share culture. The authors say it is unclear how platformization reshapes four separate things: creation, distribution, marketing and monetisation. They try to pull those four apart. At the same time they see a concentration of power (economic, infrastructural, political and cultural) in a few mostly US and Chinese firms.

Structure. Nieborg covers Part 1, institutional change, in three shifts: markets, infrastructures, governance. The test case is Zynga on Facebook. Duffy covers Part 2, changing cultural practices: labor, creativity, democracy. Her test case is the YouTuber Emma Chamberlain.

The close. Duffy says two stories compete: techno-utopianism (“platforms gave everyone the tools”) and a rising wave of critique, plus talk of “the imminent death of social media”. Her answer is to treat power as productive (a Foucauldian view). Power does not only press down from the top. It produces worker identities, duties, inequalities, “regimes of visibility” and ways of making meaning.

The Q&A (about 24 minutes). Main points: the book is slow on purpose and avoids hot topics like Musk’s Twitter and the metaverse, because things need to “sediment”. Nieborg sees intensification, not rupture. There is little research on how governance affects producers (as opposed to end users). Rules are applied unevenly and reward “brand friendliness”. Game tools are cheap but distribution is controlled by Apple and Google. Creators organise in hidden, informal networks, not unions.

Stance. Critical but not alarmist. They avoid one-size-fits-all answers. They offer a framework (a set of questions and concepts) more than a verdict.

Map — talking points

#	Point
1	Host intro: the QUB MA, the format, the book’s pitch; asks whether Musk’s Twitter takeover will be covered
2	Nieborg: guiding question; defines “platforms” and “cultural production” (what is in and out)
3	The argument: democratisation story vs concentration; four processes to pull apart; Poell credited
4	Story: Mark Pincus, Zynga, Facebook (2007 platform opening, poker, FarmVille, the wall-post spam, the break)
5	Three institutional shifts: markets (multi-sided markets), infrastructure (integration, APIs, boundary resources), governance (opening vs securing boundaries)
6	Handover. Duffy: Emma Chamberlain as a platform-dependent producer
7	Labor: individualisation, gig discourse; four tensions; the algorithm as source of fear and uncertainty; Cooper the TikToker
8	Precarity: platform evolution injects insecurity (Twitter hook)
9	Creativity: qualification vs quantification; metrics (Gitlin 1983); loss of creative control; metric industries
10	Democracy: access, diversity, protection from harm, truthfulness; McRobbie’s creative dispositif; winner-take-all; inequality maps onto gender, race, sexuality
11	Close: techno-utopianism vs critique vs “social media is dying”; power as productive (Foucault)
12	Q&A: chat disabled; Q1 What has changed since the book? Sedimentation; Musk; intensification not rupture
13	Q&A: Renan’s ethics question; Nieborg and Duffy on governance for producers; Sophie Bishop; unequal enforcement
14	Q&A: Tom Livingstone on aesthetic homogenisation; Nieborg on games, Unity/Unreal, Apple/Google, global asymmetries
15	Q&A: Kim Marie on reggae, vinyl to Spotify; continuity and the black box
16	Q&A: Dennis Murphy by email: labor organising for creators
17	Close and thanks; video to go on the QUB channel

Putting it together

The mental model in one paragraph. Cultural producers (news outlets, game studios, creators) now reach audiences and income mostly through platforms they do not control. The authors give a map in two halves. The institutional half: platforms organise markets (as multi-sided markets that decide who pays), infrastructure (APIs and boundary resources that producers must integrate with), and governance (rules that open and close access, as in the Zynga case). The practice half: these shifts change labor (individualised risk, fear of the algorithm), creativity (metrics that pull makers toward what “wins”), and democracy (cheap tools, but audiences and money still follow old hierarchies). Their key moves are to separate creation, distribution, marketing and monetisation and to see power as both institutional (set from above) and productive (shaping who creators become). The method is slow and structural: build concepts that survive changes of app. The claim is intensification, not rupture.

Three tensions to keep open

Intensification or rupture? Nieborg says the logic held through Musk’s X and the 2022 shake-up. Generative AI changes creation, the first of the four processes. Does the framework hold?
Institutional power or productive power? One suggests regulation; the other suggests culture and solidarity. The talk blends them without saying which leads.
Producers or users? The authors fill a gap on producers. But harms to audiences (addiction, misinformation) may be the bigger policy driver, and producers and users are not separate groups (everyone posts a bit).

Reading path

Start: Poell, Nieborg and Duffy, Platforms and Cultural Production (Polity, 2022): chapters 1–2 and 4. Nieborg and Poell (2018), “The platformization of cultural production”. Duffy, (Not) Getting Paid to Do What You Love (2017).
Then: Gillespie, “The politics of ‘platforms’” (2010). Helmond (2015), “The platformization of the web”. Ghazawneh and Henfridsson (2013), boundary resources. Rochet and Tirole (2003) or a short explainer on two-sided markets. McRobbie, Be Creative (2016), introduction.
Deeper: Hesmondhalgh, The Cultural Industries. Gitlin, Inside Prime Time. Bucher, If…Then. Hindman, The Myth of Digital Democracy. Foucault, Discipline and Punish and The Birth of Biopolitics. Kellogg, Valentine and Christin (2020), “Algorithms at work”. Gillespie, Custodians of the Internet.

Part 1 — Before you read

Key terms

Platform. In this book, a digital infrastructure that mediates between different groups (users, makers, advertisers) and sets rules for them. Meanings differ by field. See the table below.
Platformization. Nieborg and Poell’s working definition (2018, New Media & Society): “the penetration of economic and infrastructural extensions of online platforms into the web” and into cultural industries, which reorganises how culture is produced, distributed and circulated (summary of the article). It is a process, not a state. Duffy and Nieborg stress this word “process”.
Cultural production. Here narrowed to market-based making of symbolic goods. Sociologists such as Bourdieu use the same phrase more widely. Be careful when comparing.
Multi-sided market. A market where one firm connects two or more groups, and each group’s value depends on the other (e.g. players and game makers, advertisers and audiences). From platform economics.
Infrastructural integration. A producer must plug its tools, code and workflow into the platform’s: APIs (application programming interfaces), SDKs (software development kits), data formats.
Boundary resources. The tools and rules a platform gives outside developers (APIs, SDKs, documentation, review processes, contracts). They are where the platform decides who gets in and how. The term comes from information-systems research.
Complementor. A firm or person who makes goods that depend on a platform (a game studio, a news publisher, a creator). A term from platform strategy. Not used in the talk by name but implied by “complementer”.
Governance (platform governance). The rules, systems and enforcement by which a platform controls access to its market and infrastructure. This includes community guidelines, algorithms, payment terms and bans.
Regimes of visibility. Duffy’s phrase: the rules and algorithms that decide who is seen. Creators can be made visible or invisible by them.
Platform dependent cultural producer. A producer who relies on platforms “to generate audiences, to make revenue, and to participate in creative and democratic practices”.
Dispositif / apparatus. From Foucault. McRobbie uses it for a network of discourses, rules and institutions that shape what people do. See idea 7. (In the Citton page this word had three meanings. Here it has this one.)
Sedimentation. Nieborg’s word for the slow settling of a platform’s form and of good research about it.

Words that change meaning by field.

Word	Platform economics	Software and information systems	Media and cultural studies (this book)
Platform	A firm that runs a multi-sided market	A software base others build on (e.g. an OS, an app store)	An institution that also governs speech and visibility
Governance	Pricing and access rules	Boundary resources, API terms	Content moderation, demonetisation, algorithmic ranking
Power	Market power: pricing, lock-in	Control over interfaces	Institutional power plus Foucauldian productive power

The book’s job is to join these three. That is why it reads as a blend.

People named and implied (a reading list)

Person	Why they come up	Start with
Thomas Poell	Third author; governance chapter	The Platform Society (2018, with van Dijck and de Waal)
David Nieborg and Thomas Poell	The platformization frame	”The platformization of cultural production” (New Media & Society, 2018)
Brooke Erin Duffy	Aspirational labor, visibility labor, creator inequality	(Not) Getting Paid to Do What You Love (Yale UP, 2017)
Todd Gitlin	Ratings as an attempt to predict the unpredictable	Inside Prime Time (1983)
Angela McRobbie	The “creative dispositif”	Be Creative (Polity, 2016)
Sophie Bishop	”Brand friendliness” and the YouTube algorithm	”Anxiety, panic and self-optimization” (Convergence, 2018)
Michel Foucault	Power as productive	Discipline and Punish (1975); History of Sexuality vol. 1 (1976)
Taylor Lorenz	Journalist who profiled Chamberlain	Her 2019 Chamberlain profile (paywalled)
Mark Pincus, Mark Zuckerberg	The Zynga story	Press accounts of Zynga 2007–2013
Emma Chamberlain	Duffy’s case	Her YouTube channel; Chamberlain Coffee
”Cooper”	Interviewed TikToker	From the book’s interviews

The speakers’ own frame

Nieborg and Poell have written together since 2018. Their frame treats platformization as change in three layers: markets, infrastructures, governance. They first applied it to news and games (2018) and then added social media creators with Duffy. Duffy’s earlier work looks at aspirational labor (hoping that unpaid, passion-driven work will turn into a career) and gender. The 2022 book joins both lines and adds the cultural-practice layer: labor, creativity, democracy. A good short description from the publisher and library catalogues: the book examines how platformization affects the cultural industries, including changes in markets, infrastructures and governance, and shifts in labor, creativity and democracy; it foregrounds news, gaming and social media creation (UvA record, New Books Network). Publication year: Polity, 2022 (some catalogues say 2021; 2022 is the more consistent date).

Event. The Queen’s University Belfast events archive lists an “In Conversation” session on Platforms and Cultural Production with Duffy and Nieborg dated 7 December 2022 (QUB page). The talk’s own clues match: Musk’s takeover of Twitter (Oct 2022) and Meta’s layoffs (9 Nov 2022) are described as recent.

The current debate (2022–26)

The book’s claims are being tested against generative AI. New work treats gen AI as another step in platformization, not a break. One study of about 2 million Stable Diffusion and nearly 1 million Midjourney prompts finds prompts cluster around style and artist keywords, and describes gen-AI platforms as rent-seeking (MMU Digital Society event, 2026). A 2025 paper argues platforms’ two-sided structure makes creators’ bargaining position unequal and that gen AI reopens the question of pay for content (Creatives Unite). An April 2026 SSRN preprint argues gen AI lowers the barrier to expression but increases pressure from platform metrics (SSRN). These are abstracts, so check the full texts before citing.
Gatekeepers and the app store. Nieborg’s point that Apple and Google gatekeep mobile games has become a legal fight. In 2021 a US court found Apple’s anti-steering rules broke California law. In April 2025 a judge found Apple in civil contempt over the injunction. The Ninth Circuit’s July 2025 decision in Epic v. Google upheld wide remedies against Google (eMarketer, vLex summary). A Dec 2025 Ninth Circuit item came from one secondary source and is not confirmed.
Studying platforms needs data. Nieborg says little is known about how rules affect producers. In the EU, a delegated act under the Digital Services Act took effect on 29 Oct 2025, letting vetted researchers request data from very large platforms to study systemic risks (European Commission). That helps researchers; it is not yet creator-specific. A search found nothing creator-specific in it.
Creators are diversifying. Industry surveys say creators worry more about platform volatility and move toward owning their audience (newsletters, courses, products). One example is a Kajabi survey of 1,717 people that found concern about volatility roughly doubled in a year (NetInfluencer). Kajabi sells creator tools, so treat the numbers as marketing. This matches Duffy’s answer on spreading work across platforms.
Not searched. TikTok’s US legal status, X/Twitter after Musk, and the Threads/Bluesky split were not searched. They bear on the “death of social media” theme but are left out here.

The ideas

The talk lasts 25 minutes before Q&A and covers a lot of ground in slogans. A first-year student at QUB would hear “multi-sided markets”, “boundary resources”, “creative dispositif” and “Foucauldian” in a few minutes. This section lays out where each comes from. Eight families of ideas meet in the talk:

 POLITICAL ECONOMY OF MEDIA ─┐                  ┌── PLATFORM ECONOMICS & STRATEGY
 Adorno · Garnham · Bourdieu │                  │   Rochet-Tirole · Armstrong
 Hesmondhalgh · Gitlin       │                  │   Gawer-Cusumano · Eisenmann
                             ▼                  ▼
                     ┌─────────────────────────────────┐
 INFORMATION SYSTEMS ► │  POELL · NIEBORG · DUFFY:        │ ◄ PLATFORM & SOFTWARE STUDIES
 Tiwana · Ghazawneh   │  platformization of cultural     │   Gillespie · Helmond · Srnicek
 Henfridsson (boundary│  production: markets,            │   van Dijck · Plantin
 resources)           │  infrastructures, governance     │
                     │  → labor · creativity · democracy│
                     └─────────────────────────────────┘
                       ▲            ▲            ▲
 CREATIVE LABOR & PRECARITY │  METRICS, ALGORITHMS & │  DEMOCRACY, INEQUALITY
 McRobbie · Neff · Gill     │  VISIBILITY            │  & INTERSECTIONAL CRITIQUE
 Duffy · Abidin · Standing  │  Gitlin · Bucher · Cotter│ Hindman · Noble · Bishop
                            │  Espeland-Sauder       │ Benkler · Jenkins
                                         POWER: Foucault → governmentality → "entrepreneurial self"

Where each school of thought is covered:

Political economy of media and the cultural industries: idea 1
Platform economics — multi-sided markets and platform strategy: idea 2
Information systems — infrastructure and boundary resources: idea 3
Platform and software studies — politics, algorithms, society: idea 5
Creative labor, precarity and aspirational work: idea 4
Metrics, quantification and algorithmic culture: idea 6
Power — Foucault and the entrepreneurial self: idea 7
Democracy, inequality and the “democratisation” promise: idea 7
Where the traditions meet (summary table): idea 8

1. The question, the scope and the four processes

In short. Nieborg asks what it means, politically, economically, culturally and socially, that cultural production now depends on platforms. He limits the scope to platform companies at the heart of the cultural and media industries, such as Google, Apple, Meta and Chinese platforms. He is less interested in Airbnb or Uber, and the focus is market-based production of symbolic artifacts.

🎙 In the talk. Nieborg asks “what are the political or political economic and cultural and social implications of cultural production becoming platform dependent”. He fixes scope first: “platform companies that are at the heart of the cultural or media industries”, so Google, Apple, Meta and Chinese platforms, and “less interested in your Airbnbs and Ubers because they’re not at the heart yet or maybe they never will” of cultural production. “Cultural production” means “market-based cultural production of symbolic artifacts” by organisations or individuals, and he says everyday users are “less relevant only to keep the book manageable”.

The argument: platforms are “long associated… with a discourse of democratization”, and “it’s easier supposedly than ever to create and distribute cultural content”. But “it remains unclear” how platformization reshapes “creation and distribution and marketing and monetization”, so “one thing that we try to do in the book consistently is to pull those apart”. It is “a process” that is “ongoing”, “contingent” and “fluid”. At the same time there is “a concentration of power… economic and infrastructural and political cultural power among very few mostly US-based and China-based corporations”.

📚 Deeper theory

Why “pull apart” four processes. In older media, one firm often did all four: a studio made, sold, marketed and monetised a film. Platform firms usually do distribution and monetisation (and some marketing), not creation. A platform can therefore be easy to enter (creation and upload are free) and hard to succeed on (visibility and income are not). The democratisation story merges these steps. The framework separates them (see Roots, idea 7).
The scope choice has a cost. Leaving out Uber and Airbnb keeps the study on culture and media. It also leaves out the labor-platform literature (Gray and Suri; Rosenblat) where many of the same dynamics appear (see idea 4). Duffy’s later “gig” language pulls it back in.
Why “platform dependent”. The idea of dependence comes from resource dependence theory (Pfeffer and Salancik, 1978; from memory): an organisation that relies on a resource it does not control becomes subject to whoever controls it. Platform dependence is that, applied to audiences and distribution.
“Process”, not “stage”. Nieborg and Poell reject a story in which platforms replace old industries once. They stress continuing change, which is why the book later resists writing about Musk or the metaverse (idea 9).
Bourdieu check. “Cultural production” in Bourdieu’s sense includes avant-garde work that deliberately refuses the market. The authors’ narrower sense means a reader cannot extend their findings to non-market art without care.

📚 Roots: Political economy of media and the cultural industries

The problem. Who owns and controls the means of making and spreading culture, and does that shape what gets made? This is the home field of Nieborg and Poell. They call themselves political economists (Nieborg: “the political economist in me”).

The point. The “concentration” worry is an old political-economy worry (few owners, much reach). The new point is that platforms concentrate power through infrastructure and rules, not by owning content. Platforms rarely commission content, so their power cannot be read from ownership lists. That is why the talk keeps pairing “economic” with “infrastructural” power.

The chain of thinkers

Theodor Adorno and Max Horkheimer, “The Culture Industry” (1944/47). Culture made by firms for mass sale is standardised, like a factory product. The word culture industry is the ancestor of this whole field. Later scholars refine or reject their gloom.
Pierre Bourdieu, The Field of Cultural Production (essays 1983–93). Culture is made in a field with its own rules. He splits a restricted field (art for peers, prestige) from a large-scale field (art for sale). The book’s title echoes his phrase, though the book narrows “cultural production” to market-based work.
Nicholas Garnham (1990) and David Hesmondhalgh, The Cultural Industries (1st ed. 2002; later editions). Hesmondhalgh gives the standard modern account. He shows that cultural firms face a special problem: the product is risky (hits are unpredictable) and cheap to copy. So firms use tools to manage risk: stars, formats, genres, tight control of distribution, and a “complex professional” model that gives makers some freedom while owners control marketing and distribution.
Paul Hirsch (1972), “Processing Fads and Fashions”. Cultural goods pass through gatekeepers (publishers, programmers, critics). Overload of new goods gives power to those who select.
Todd Gitlin, Inside Prime Time (1983). US TV executives do not know what will succeed. They use ratings, copying and formulas to make decisions look rational. Duffy cites him for the idea that ratings try “to predict the unpredictable”. William Goldman’s line “nobody knows anything” (about Hollywood, 1983) is the folk version. (Goldman†)
Richard Caves, Creative Industries (2000). Applies contract theory to creative work and names the “nobody knows” property of hits.
Poell, Nieborg and Duffy. They add one new fact. A second layer of gatekeeper has appeared that is not a cultural firm: a platform that sets rules for everyone and also sells to all sides.

Where others push back.

Some critics say a focus on firms and markets misses what people do with platforms: fan communities, non-market sharing and play (Jenkins; Burgess and Green on YouTube; Postigo on fans). Duffy and Nieborg decide on purpose to bracket this.
Platform studies colleagues ask whether “platform” is a useful single category across news, games and creators (Gillespie; Helmond). The book answers by giving three industries, but the risk of over-generalising remains. Nieborg himself says “not a one-size-fits-all”.

What they leave out. Non-Western platforms in detail, though the opening says “China-based”; amateur and non-commercial production; the audience side.

Check yourself

Name the four processes the authors want to separate. Why does separating them weaken the “democratisation” story?
Why do they leave out Airbnb and Uber?
What does “platform dependent” add to the older idea of “gatekeeper”?

2. The Zynga story: how a platform sets the terms

In short. Nieborg tells the Zynga story. Zynga built poker and then FarmVille on Facebook’s infrastructure and social graph, and sharing virtual goods turned Facebook into one giant marketing machine for it. Then non-players got annoyed by wall spam, and Zuckerberg said no more and cut the wall posting. Zynga’s stock price never recovered, and the lesson is that the platform sets the terms.

🎙 In the talk. Nieborg tells it as a “short story”. Mark Pincus saw Facebook rising in 2007, when it had “tens of millions of users mostly college students in the US”, and Mark Zuckerberg said Facebook wanted to be “a platform for new businesses”. Zynga published a poker game that “tapped into the infrastructure of Facebook”, so “you could play poker against your Facebook friends and earn virtual money” (not real money). Then came FarmVille, “a very simple farm simulation game that again used the Facebook social graph”. The novelty was not the game but the sharing of virtual goods with friends, “posted on your wall”. So “Facebook allowed Zynga… to essentially be one giant marketing machine”. Non-players got annoyed by “spamming” of their walls, so “Mark Zuckerberg said no more” and cut the wall posting. “The stock price of Zynga… sort of never recovered” and it was only recently acquired.

The lesson: to see how production becomes platform dependent, look at shifts in markets, infrastructure and governance.

📚 Deeper theory

A model of platform life cycle. Platform owners often start generous (to attract complementors) and tighten later (to capture value). Cory Doctorow’s popular word is “enshittification” (2022–23; from memory). The academic version is the openness trade-off in Eisenmann et al. (Roots). Zynga is the early classic. Facebook’s own accounts of its policy changes gave different reasons (spam, user experience, and its own payment and game plans).
Viral channel = a dependency. Zynga’s growth came from a distribution channel it did not own (the Facebook feed). Growth hacks built on a platform feature are reversible by the platform. This applies to news publishers (Facebook’s 2013–18 “pivot to video” and 2018 News Feed change; from memory) and to creators on algorithm shifts.
What the record adds. Search results show the break was gradual: a revised deal in Nov 2012, loss of feed sharing from 31 Mar 2013, a roughly 13% share fall on the news (The Register). One source said about 80% of Zynga revenue came from Facebook users. (Single-source figure.) Take-Two bought Zynga for about $12.7 billion in 2022 (TechCrunch), so “never recovered” fits for a decade but ended with a large exit.
Counterfactual. Would a different game have survived? Zynga also spent heavily on its own growth and had weak diversification. The story shows dependence but does not prove cause of its stock fall. This is a point of method: a single case is a strong illustration, a weak test.

📚 Roots: Platform economics — multi-sided markets and platform strategy

The problem. How do firms that bring two groups together price and grow? Why do they tend to become giants?

The point. Zynga’s story is a textbook case. Facebook subsidised developers to grow its user base (2007), then tightened terms when it needed to protect the feed and its own revenue. A producer could not choose its own business model; it “had to follow Facebook’s economic rules”. Platform economics explains why a platform behaves like this. The authors’ addition is to ask what the same behaviour does to cultural goods and workers, which standard theory mostly ignores.

The chain of thinkers

Michael Katz and Carl Shapiro (1985), network externalities. A product becomes more valuable as more people use it. This produces tipping and winner-take-most results.
Jean-Charles Rochet and Jean Tirole (2003), “Platform competition in two-sided markets”; Mark Armstrong (2006), “Competition in two-sided markets”. The core theory. In a two-sided market, the platform picks a price structure (who pays how much), not only a price level. It often subsidises one side to attract the other (e.g. free for players, charge advertisers). Tirole later won the Nobel (2014) for work on market power and regulation. Nieborg: “it’s not our idea… concept and theory comes from economics”, and mainstream economics fills chapter 2.
Annabelle Gawer and Michael Cusumano, Platform Leadership (2002); Gawer (2009, 2014). Platforms as technological bases that others build on. Owners must keep outsiders (complementors) motivated while keeping control. This is the open but not too open tension.
Thomas Eisenmann, Geoffrey Parker and Marshall Van Alstyne (2006, 2009). “Strategies for two-sided markets” and “Opening platforms: how, when and why?“. A platform owner decides how open to be. Opening grows the ecosystem; closing protects control and profit. They also warn of “envelopment”: a platform entering its complementors’ space.
Geoffrey Parker, Marshall Van Alstyne and Sangeet Choudary, Platform Revolution (2016). A popular business text that spread the vocabulary.
Jacobides, Cennamo and Gawer (2018). Ecosystems and modularity: who captures value when many firms depend on one platform.

Where others push back. Strategy scholars note that complementors can gain a lot from a platform, including large firms like Zynga, which IPO’d in 2011. The relationship is a trade, not only a loss. Some readers say the story blames Facebook for what was also Zynga’s strategy.

What they leave out. The audience’s role (Nieborg mentions users were annoyed, but not how users’ interests shape governance); the later Zynga strategy of buying studios and moving to mobile, which is a form of escaping platform dependence.

Check yourself

What did Zynga gain from integrating with Facebook? What did it lose?
Why is the Zynga ending more complex than “Zuckerberg kicked them off”?
What does this case show about the limits of a single case study?

3. Markets, infrastructure, governance: three layers of institutional power

In short. Nieborg draws three shifts from Zynga. Markets: a platform is a multi-sided market, and Zynga could not pick its own business model but had to follow Facebook’s economic rules. Infrastructure: a complementor must align its APIs and tools with the platform, which decides who gets access. Governance: platforms want to be open to an extent but also to secure their boundaries, so there is constant push and pull.

🎙 In the talk. Nieborg uses Zynga to present three shifts and their concepts.

Markets. “Every platform creates markets in a different way than conglomerates have done in the past”. He calls them multi-sided markets: “it connects at least two sides”, demand and supply, and sometimes advertisers. The power point: Zynga “could not pick its own business model… it had to follow Facebook’s economic rules”.
Infrastructure. Playing FarmVille meant going to Facebook; it ran in “Flash or HTML stuff that ran on top of Facebook”. He calls this infrastructural integration: a complementor must “align” its “APIs, software development kits, production processes” with the platform’s. To do so they use boundary resources, a term “from Information System Theory”. “Who determines who has access to the tools and how the tools work, that’s of course the platform.”
Governance. “Platforms have an incentive to secure their boundaries” (access to infrastructure and market). They “want to be open to an extent”, but there are limits, and there’s “that constant push and pull opening and securing of boundaries”. Zynga shows “what happens if that goes wrong and a platform owner like Zuckerberg is overzealous”.

📚 Deeper theory

Why three layers. It is an analytical split, not a claim that they are separate in practice. Markets = how money and demand are organised. Infrastructure = the technical base. Governance = rules, moderation, enforcement. The same change can touch all three: a rule that bans wall posts changes the market (reach), infrastructure (API behaviour) and governance (policy).
Two uses of “infrastructure”. In Star and Ruhleder’s sense, infrastructure is what you stop noticing. In platform strategy, it is a control point. The book uses the second, with some of the first (APIs matter most when they change).
Multi-sided economics and cultural goods. Standard theory treats the “supply side” as a pool of identical complementors. Cultural goods differ: one hit is worth far more than many ordinary items, and quality cannot be judged before use. This is why the curation and visibility rules (algorithms) matter so much in culture, and why Duffy’s second part is needed.
API changes as policy. The Facebook Platform’s changes (2010–15) and Twitter’s API restrictions (notably 2018 and 2023) show that technical access is policy. Twitter ended free API access in 2023†, a case after the talk that fits Nieborg’s point.
“Open” as strategy. Platforms do not just fight regulation; they also use openness as marketing (e.g. open APIs, open-source frameworks). Openness and control are managed together.

📚 Roots: Information systems — infrastructure and boundary resources

The problem. If others build on your software, how do you control and also encourage them? This literature looks at APIs and developer tools as management devices.

The point. Nieborg names the field as outside media studies’ usual reading: “Information System Theory, not necessarily a field we would be familiar with”. The lesson for a media student: to understand who has power over cultural producers, read the developer documentation. Who may call the API, who approves an app, what changed in version 2? This is also why Nieborg later says media scholars “have not been trained” to access an API, so few studies exist.

The chain

Susan Leigh Star and Karen Ruhleder (1996), “Steps toward an ecology of infrastructure”. Infrastructure is invisible until it breaks and is relational (what counts as infrastructure depends on who uses it).
Amrit Tiwana et al. (2010), “Platform ecosystems”. Splits a platform into a core and peripheral modules and asks who decides.
Amir Ghazawneh and Ola Henfridsson (2013), “Balancing platform control and external contribution in third-party development: the boundary resources model”. The source of the term. Boundary resources are the interfaces and policies through which the owner exerts control and the outsiders exert contribution. They are “the place where power is negotiated”.
Anne Helmond (2015), “The platformization of the web: making web data platform ready”. Bridges this literature to media studies. Platforms push their data formats, buttons and APIs out onto the web so that outside sites become “platform ready”. Nieborg and Poell take the term “platformization” and its infrastructural half from her.

Where others push back. Information-systems researchers sometimes argue that boundary resources also enable complementors to push back and shape the platform (Ghazawneh and Henfridsson’s own model has two-way flows). Nieborg describes only one direction. Media scholars like Gillespie argue that governance includes cultural norms and public pressure, not only business rules.

What they leave out. In the talk, state regulation (competition and platform laws) is hardly touched in Part 1, though it is now a main route of change (see “Current debate”).

Check yourself

Give one example from Zynga for each of markets, infrastructure and governance.
What is a boundary resource? Give two examples from games or news.
Why do platforms want to be “open to an extent”?

4. Emma Chamberlain and platform-dependent labor

In short. Duffy uses one case, Emma Chamberlain, a YouTuber with millions of subscribers, brand deals and a coffee line. She is known for candour and relatability and has made inroads into legacy media. The case sits at the crossing of many changes in cultural work, and media talk about young people wanting to be YouTubers shows barely concealed alarmism.

🎙 In the talk. Duffy opens with a single case “situated at the intersection of a bunch of transformations”. Chamberlain was “dubbed the most important YouTuber today according to Taylor Lorenz” in 2019, has “more than I checked last night 11.9 million subscribers”, an estimated income of “1.7” annually (unit not clear), brand deals with Audible, Curology and Hollister, and a coffee line. She is known for “candor… relatability… authenticity” and has a “rags to riches story for the social media era”, with a “jarring style that defies the more polished conventions” of traditional media, yet she has “made considerable inroads into legacy media industries” (Vanity Fair, Harper’s Bazaar). Media talk of “more young people want to be YouTubers than astronauts” shows “barely concealed alarmism”.

She is a platform dependent cultural producer who relies on platforms “to generate audiences, to make revenue and to participate in creative and democratic practices”. Platforms “really hype this ideal of creativity” even as Meta lays off “an unprecedented 13” percent (a caption fragment). Yet “platform dependent creative careers involve more than pluck and luck. They require labor.” Chamberlain has been candid: “I’ve cried multiple times after posting a video… I don’t know how I’m still alive”, and she took a six-month break for mental health. Duffy’s point: “a lot of invisible activities… required to become a hyper-visible social media personality”. Chamberlain quit TikTok because of “the addictive nature of the algorithms”, and said she did not fear being banned by an algorithm because “her community would follow her to whatever the next platform would be”. Duffy calls that “a unique point”.

📚 Deeper theory

Aspirational labor in action. Duffy’s own concept (Roots). Chamberlain is already successful, so she is an unusual case. Duffy picks her to show that even success carries cost and risk. The paradox of “work disguised as leisure” is a main theme of her 2017 book.
Authenticity as work. Scholars of influencer culture (Abidin; Marwick, Status Update 2013; Duffy and Hund 2015) show that “being authentic” is a managed performance with real labor and a market value. Chamberlain’s “unpolished” look is an aesthetic choice that is also a brand. That is not a charge of fakery; it is a claim that the work behind it is hidden.
Why the TikTok remark matters. Her comment that her audience would follow her suggests a portable audience. This is rare. Most creators cannot move audiences (platform lock-in; network effects, idea 2). It marks the difference between an elite creator with a strong personal brand and the typical case, a point Duffy makes with Cooper next.
Mental health and burnout. Research on creator burnout (Duffy and Meisner 2022; from memory) links it to the constant-visibility demand (“always on”). Crary’s 24/7 is a wider frame.
The “dream job” story. Surveys report that many young people want to be influencers (the “YouTubers vs astronauts” line, 2019, was a popular survey claim; not verified here). The authors’ point is that the job exists but pays very unequally, which the next sections develop.

📚 Roots: Creative labor, precarity and aspirational work

The problem. Are creative jobs a privilege or a trap? Why do people accept unstable pay for “passion”?

The point. Duffy’s four tensions (visibility/invisibility, collective/individual responsibility, security/precarity, equality/inequality) read as a summary of this literature. Her Chamberlain case is chosen to show the paradox at the centre of Duffy’s earlier work: a lot of hidden effort is needed to look effortless. Her claim that these labor patterns are not new but exacerbated is the standard scholars’ line against “the gig economy changed everything”.

Angela McRobbie, Be Creative: Making a Living in the New Culture Industries (2016). Young people are urged to “be creative” as a way to escape routine work, but they end up self-employed, unprotected and competing. She uses the term creative dispositif (after Foucault) for the web of policy, talk and institutions that produces this. Duffy borrows it.
Gina Neff, Elizabeth Wissinger and Sharon Zukin (2005), “Entrepreneurial labor among cultural producers”. Models and dot-com workers took risk on themselves in hope of future reward.
Rosalind Gill and Andy Pratt (2008), “Precarity and cultural work”; Guy Standing, The Precariat (2011). Name the shift from stable jobs to insecure work.
Kuehn and Corrigan (2013), “hope labor”; Duffy (2017), “aspirational labor”. Duffy’s term. Young women (fashion bloggers) work unpaid hoping to turn passion into a career. The work is both real and unrewarded.
Crystal Abidin (2016), “visibility labour”; Abidin, Internet Celebrity (2018). Effort spent making oneself seen in a way the platform and brands will reward.
Duffy, Pinch, Sannon and Sawey (2021), “The nested precarities of creative labor on social media”. Layers of precarity: the job, the platform, the market, the self. (Authors and year†)
Terranova (2000), “Free Labor”. Users’ unpaid activity as value for firms. Background to why a “creator economy” can be cheap to platforms.
Rosenblat and Stark; Kellogg, Valentine and Christin (2020); Gray and Suri (2019). The wider gig and “algorithmic management” research, which is why Duffy ties creator labor to the gig discourse.

Where others push back. Case selection: one star creator can mislead. Chamberlain’s income is far above typical. Duffy knows this and uses her as an entry to the structure. Some scholars would say the amateur and mid-tier creator (most of the field) tells the real story. The book has interviews with such creators (e.g. Cooper). Another critique: an income estimate from a social media analytics site is soft data.

What they leave out. Platform revenue-sharing rules specific to YouTube (e.g. the YouTube Partner Programme thresholds; Postigo 2016) are not discussed in the talk, though they structure the work. The role of managers, agencies and multi-channel networks is also left out.

Check yourself

Why does Duffy choose a successful creator to show precarity?
What is the “paradox” of visibility and invisibility?
Why is Chamberlain’s remark about her audience following her unusual?

5. Labor: four tensions and the algorithm

In short. Duffy says cultural work has been transformed by individualisation, which pushes risk from corporations onto individuals. Add the gig economy and talk that everyone should be their own boss. These practices are not new, but platforms intensify them. The book explores four tensions: visibility and invisibility, collective and individual responsibility, job security and precarity, and equality and inequality.

🎙 In the talk. Labor in cultural production has been “transformed through the individualization of work” which “offsets risk from corporations onto individuals”, plus “the rise of the gig economy” and “pervasive discourses of entrepreneurship where everyone wants to be their own boss”. The labor practices “are not new but they are exacerbated or intensified by the rise of platforms”. The book explores four tensions: “visibility and invisibility, collective and individual responsibility, job security and precarity, and equality and inequality”.

She illustrates with “the mystique surrounding the algorithm”. Many cultural producers “live in this sort of fear of the algorithm not just rendering them visible but rendering them invisible”. Cooper, a TikToker, says: “the unpredictability of the algorithm… you’ll go through a week or two where your views are half of what they were… even if your content production isn’t changing you have no way of knowing how things work”. So creators “spend a considerable amount of time behind the scenes trying to make sense of how the algorithm works” and “platforms’ regimes of visibility have structured so much uncertainty into these careers”. She links this to current events: what does Twitter’s shake-up mean for creators whose livelihoods are dependent upon… these regimes of visibility?

📚 Deeper theory

Risk transfer. The sociology of work calls this individualisation of risk (Beck, Risk Society, 1986; Standing, 2011). Firms move uncertainty (demand, illness, training) to workers. Platforms add algorithmic uncertainty on top: you are an independent worker but with a boss you cannot talk to.
The algorithm as a “boss”. In algorithmic management research (Kellogg et al., 2020), platforms direct, evaluate and discipline workers using data. The same toolkit works on creators, though they are called “partners” not employees. The six levers (restricting, recommending, recording, rating, replacing, rewarding) from Kellogg et al. map onto demonetisation, recommendations, analytics, ranking and payouts. (Details from memory.)
Folk theories. Where rules are hidden, people build explanations (Bucher, Cotter, Bishop; Roots). This creates a market for tips and courses. Duffy mentions a “cottage industry” of tool sellers.
Nested precarity. Creator risk exists at several levels: the platform may change, brands may drop you, the audience may tire, and your body may fail (the Chamberlain break). See Duffy et al. (2021).
Why “not new”. Cultural work was precarious before platforms: freelancers, actors, session musicians (Ross; Hesmondhalgh and Baker 2011). What platforms change is who the intermediary is, how visible the competition is and how data-driven the feedback.
“Collective vs individual responsibility”. Platforms shift responsibility for success onto the individual (“work harder, optimise”) and so weaken the case for collective action. This leads to the union question (idea 12).

📚 Roots: Platform and software studies — politics, algorithms, society

The problem. Platforms present themselves as neutral pipes. These scholars ask what they really do.

The point. Duffy’s Part 2 picks up where Bucher and Bishop leave off. Her contribution is to move the algorithm from a user problem to a producer problem. The talk’s only strong claim about literature is that this move is under-researched.

Tarleton Gillespie, “The politics of ‘platforms’” (2010). The word platform is a rhetorical choice. It sounds flat, open and neutral. This hides editorial power. Later: Custodians of the Internet (2018) on moderation as the core product of platforms.
Nick Srnicek, Platform Capitalism (2016). Platforms as a business model that extracts and owns data. Some of his types (advertising, cloud, lean) are used in the book’s economic side.
José van Dijck, Thomas Poell and Martijn de Waal, The Platform Society (2018). Poell’s earlier book. It argues that platforms now intertwine with public values (health, education, news, transport). It introduces the three-layer vocabulary: data, algorithms, interfaces; ownership, governance, business models.
Jean-Christophe Plantin, Carl Lagoze, Paul Edwards and Christian Sandvig (2018), “Infrastructure studies meet platform studies in the age of Google and Facebook”. Argues that platforms and infrastructures are merging: platforms behave like infrastructures that everyone needs.
Taina Bucher (2012), “Want to be on the top?”; If…Then (2018). The “threat of invisibility”: on Facebook, being unseen is the penalty. This is the root of Duffy’s “regimes of visibility” and of creators’ fear.
Kelley Cotter (2019), “Playing the visibility game”; Sophie Bishop (2018, 2019), “algorithmic gossip”. Creators build folk theories of the algorithm and trade them. Duffy’s quote from Cooper (“you have no way of knowing how things work”) is a clean example.
Robert Gorwa (2019), “What is platform governance?“. Defines the sub-field Poell’s chapter 4 works in.

Where others push back. Some researchers find creators more agentive than this suggests: they use platforms strategically, switch, and gain real power with large audiences (Cunningham and Craig, Social Media Entertainment, 2019, take a more mixed view). Others argue that “precarity” may be overused: some creators choose flexible work knowingly. Duffy’s “tension” language leaves room for both.

What they leave out. Global differences: creators in India, Nigeria or Brazil face different payouts, currencies and platform support. The talk’s examples are US-centred (Cooper’s location is not given).

Check yourself

List the four tensions. Give one concrete example of each from the talk.
How is algorithmic uncertainty different from ordinary freelance uncertainty?
Why might “folk theories” of the algorithm be a form of unpaid work?

6. Creativity and the metric logic

In short. Duffy takes the tension between qualification and quantification. Metrics are not new: she cites Gitlin on TV ratings as an attempt to predict the unpredictable. What is new is the constant demand to make work that earns likes and comments. Producers feel they lose creative control, because the question shifts from what they want to put out to what will win the algorithm.

🎙 In the talk. Creativity is not “a singular concept” but “a tension that circulates as a more long-standing force between creative expression and commercial tensions”. The book explores four such tensions; Duffy picks qualification and quantification. “We think of metrics as something that is born of the digital age”, but she cites Todd Gitlin (1983) on TV ratings as “an attempt to predict the unpredictable… we don’t actually know how people are going to respond to any given cultural product”. What is new: “cultural producers face this kind of incessant demand to produce work that does well attracting likes, favorites, comments”, which “triggers a perceived loss of creative control”: no longer “this is the product that I want to put out there” but “what’s going to do well… win the algorithm”. Metrics are not only used by platforms but “by various other players… from influencer industries to the cultural workers who track performances to various new kind of cottage industry players who are trying to sell us the tools and tactics of how to win the algorithm”.

📚 Deeper theory

Reactivity. Espeland and Sauder: measures change the thing measured. A like-count is not a mirror; it is a lever on behaviour (Roots).
Why old ratings differ from platform metrics. Ratings were aggregate and delayed, bought by a few firms (Nielsen). Platform analytics are individual, instant and public (anyone sees the like counter). That raises both the speed of feedback and the social pressure. Also, the metric is tied to money (payout) and reach (ranking) in the same system.
Contingent commodity. For Nieborg and Poell (2018) the cultural item is contingent: it is changed and tested constantly, e.g. news headlines, game updates and in-app purchases. Quantification does not only measure the product; it helps make it.
Convergent style. If many creators optimise for the same signals, their work may converge. This links to Tom Livingstone’s question (idea 11) and to Kyle Chayka’s Filterworld (2024), which argues algorithmic feeds flatten taste. (†)
Defence of metrics. Metrics also tell small creators what works and allow them to find audiences without a gatekeeper. The older “gatekeeper” system was biased too, in other ways. Both sides are real.
Generative AI link. If tools make content cheaply, the metric pressure gets larger: more supply, same attention. This is the thread in recent studies (see “Current debate”).

📚 Roots: Metrics, quantification and algorithmic culture

The problem. When art meets numbers, what happens to art?

The point. Duffy’s “qualification and quantification” tension puts a long-standing tension (art vs numbers) into a platform setting. Her point of difference: before, metrics were periodic (a rating each week); now they are continuous and public, and a whole side industry sells tactics and tools to “win the algorithm”.

Ien Ang, Desperately Seeking the Audience (1991); Philip Napoli, Audience Evolution (2011). Audiences are made visible to industry through measurement. The “audience” is a product of the measure itself.
Gitlin (1983). See idea 1: ratings are a way to manage uncertainty, not remove it.
Donald Campbell (1979) and Charles Goodhart (1975). When a measure becomes a target, it stops being a good measure. Known as Campbell’s and Goodhart’s laws.
Wendy Espeland and Michael Sauder (2007), “Rankings and reactivity”. People change behaviour because they are measured. Law schools reorganised around the US News ranking. Creators do the same with likes and views.
Theodore Porter, Trust in Numbers (1995). Numbers are used when people lack trust and need to be seen as neutral.
Ted Striphas (2015), “Algorithmic culture”; Hallinan and Striphas (2016), on Netflix. The decision about what is culturally “good” moves to computation.
David Beer, Metric Power (2016). Measures are a form of power in their own right.
Nieborg and Poell (2018), “contingent cultural commodity”. The cultural good is never final: it is updated, A/B-tested and tied to data, so its form depends on platform signals. This is the economic version of Duffy’s “loss of creative control”.

Where others push back. Some say the contrast of “creative expression vs commerce” is itself romantic. Many artists always worked for patrons and markets (Hesmondhalgh, Becker’s Art Worlds, 1982; from memory). Duffy’s wording as a tension (not a loss) fits this. Some also argue that metrics can help creative learning.

What they leave out. Detail on how specific metrics (watch time vs likes) differ and shape different styles; the role of the audience in feeding numbers; what happens to creators who ignore metrics.

Check yourself

What did Gitlin’s ratings do, and how do platform metrics differ?
What is “reactivity”? Give a creator example.
What is the “cottage industry” Duffy mentions, and why does it exist?

7. Democracy, access and the “creative dispositif”

In short. Duffy says platform companies hype the ideal that social media is inherently democratic and open to all. She calls this the creative dispositif, after McRobbie. The talk of equal access hides hierarchies. The system is winner-take-all, and its inequalities follow gender, race, sexuality and ethnicity, in a space that compels everyone to be platformed.

🎙 In the talk. The book discusses a series of ideals including access, diversity, protection… from harms, and truthfulness; Duffy focuses on access and diversity. The popular idea is that “anyone has access to the tools to create content, to go viral, anyone can create a post online and become an independent journalist”. She draws on Angela McRobbie’s “creative dispositif”: platform companies “hype the ideal” that “social media platforms are inherently democratic”, “a path to career success accessible to all”. But “this discourse of equal access and opportunity effectively obfuscates the hierarchies and inequalities”. There are “stark inequalities”, a “winner-take-all system”, and the inequalities “map onto traditional social structures: gender, race, sexuality, ethnicity”. “Among influencers and creators in particular there are striking imbalances in compensation from ad sponsors to the platforms themselves to the way audiences treat these creators” in “a space that compels everyone to be platformed… platform visible”.

📚 Deeper theory

Access to tools vs access to audiences. Cheap tools lower the cost of entry. Success still depends on being found. Hindman (2009) showed online attention is steeply unequal even when publishing is free (Roots). This is the long tail debate: the tail is long but earns little.
Why inequality tracks old lines. Reasons: brands choose creators who fit certain looks; audiences reward some bodies and voices more than others; platform rules can penalise identity terms; and creators with money or a network start with advantages. Studies (Duffy; Bishop; Noble; Are) show these routes. Pay-gap data from crowdsourced sheets (see idea 10) gives a bottom-up check.
“Platformed”. Duffy’s phrase “compels everyone to be platformed” resembles compulsory visibility. Opting out has a cost (lost jobs, lost reach). Not being online is no longer neutral for cultural workers.
Dispositif. For McRobbie and Foucault, a dispositif joins talk, rules, buildings and habits into one system that produces a kind of person (Roots). The creative dispositif says: do what you love, be your own brand, and the market will reward you. That story is a soft form of governance.
The other three ideals. Protection from harm connects to moderation and online abuse. Truthfulness connects to news and misinformation (the news half of the book). In the talk they are named, not developed.
Political-economy check. Greater diversity of makers does not always give greater diversity of output: economists have shown that concentrated platforms can make a long tail and a few superstars at once (Anderson vs Elberse, Blockbusters, 2013; from memory).

📚 Roots: Power — Foucault and the entrepreneurial self

The problem. The talk ends on power “that is not just top down”. This needs a short explanation because it quietly changes the whole argument.

The point. Duffy offers “power as productive” to reconcile two stories (utopian vs critical). Platforms do not just cap what creators can do. They produce a particular kind of creator: self-managing, visible, metric-aware, grateful for access. This is why the book can say both “democratisation” and “concentration” are true.

Steven Lukes, Power: A Radical View (1974). Three faces of power: making people do things, setting the agenda, and shaping what people want. Useful as a baseline.
Michel Foucault, Discipline and Punish (1975) and History of Sexuality, vol. 1 (1976). Power is not mainly a thing a ruler has. It works through institutions, norms and knowledge, and it produces subjects: kinds of people who govern themselves. “Productive power” means power that makes things (identities, habits, truths), not just forbids.
Foucault, lectures on The Birth of Biopolitics (1978–79). Neoliberalism asks people to see themselves as enterprises, “entrepreneurs of themselves”. Later work: Ulrich Bröckling, The Entrepreneurial Self (2016); Nikolas Rose on governing through freedom.
Governmentality (Foucault, 1978). Power as “conduct of conduct”: shaping choices from a distance.
McRobbie’s creative dispositif (idea 4) applies this to the cultural sector.
Competing view — structural or institutional power. Barnett and Duvall (2005) separate compulsory, institutional, structural and productive power. Nieborg’s Part 1 (who sets the rules, who owns the infrastructure) is institutional and structural. Duffy’s closing move adds productive. The talk joins both in one frame without saying that these traditions often argue.

📚 Roots: Democracy, inequality and the “democratisation” promise

The problem. The internet was sold as a way for anyone to publish. Did that happen?

The point. Duffy’s argument runs: access to tools is wide, but access to audiences and income is not, and the gap tracks old hierarchies. Nieborg repeats it for games: you can make a game anywhere, but the money still lands in the old centres.

Yochai Benkler, The Wealth of Networks (2006); Henry Jenkins, Convergence Culture (2006); Chris Anderson, The Long Tail (2006). The optimist canon. Cheap tools let ordinary people make and share culture; niche goods can live.
Fred Turner, From Counterculture to Cyberculture (2006); Richard Barbrook and Andy Cameron, “The Californian Ideology” (1995). Where the freedom-and-tech story comes from.
Matthew Hindman, The Myth of Digital Democracy (2009). Attention online is highly concentrated; links and visits follow power laws. The “winner-take-all” Duffy mentions has long roots in Sherwin Rosen (1981), “The economics of superstars”, Robert Frank and Philip Cook, The Winner-Take-All Society (1995), and Salganik, Dodds and Watts (2006) on social influence in a music market.
Safiya Noble, Algorithms of Oppression (2018); Ruha Benjamin, Race After Technology (2019). Algorithms reproduce racial and gender bias. The creators of colour in Duffy’s anecdote fit this line.
Sophie Bishop (2018, 2021) on brand safety, “algorithmic gossip” and the way advertiser-friendly values shape visibility.
Carolina Are (2022) and others on shadowbanning and moderation that hits sex workers, pole dancers and LGBTQ creators harder. (†)
The book’s four ideals (access, diversity, protection from harm, truthfulness) come from media policy debates about what a media system should deliver. The exact list is the authors’.

Where others push back. Optimists (Jenkins; Burgess and Green) note real gains: voices that traditional media excluded can now reach audiences (e.g. LGBTQ and disabled creators; regional-language creators). A balanced view holds both: more entry and new barriers. Duffy’s framing as a “tension” stays on that line, but her tone in the talk leans critical.

What they leave out. Concrete evidence in the talk itself for the pay gaps (pointers only; the book has data). Differences by country. Positive examples where platforms did widen access.

Check yourself

What is the difference between access to tools and access to audiences?
What is a “dispositif”, and what is the “creative” one?
Name two reasons why inequality on platforms follows older social lines.

8. Power as productive: the closing frame

In short. Duffy sets techno-utopianism against critiques of big tech, and notes the recent predictions that social media is ending. To reconcile them she thinks of power as not just top down but productive, in a Foucauldian sense. It produces worker subjectivities and responsibilities, forms of inequality, regimes of visibility and ways of making meaning that will keep shifting.

🎙 In the talk. Duffy asks how to read the changes. “On one hand” there is “techno-utopianism… that platforms have dramatically reconfigured the culture industries by giving everyone the tools to create and monetize content and have equal access”. This story “has been very productively problematized in recent years and kind of brushes up against… critiques of big tech”, and in “the past month… a lot of predictions that social media is ending… the imminent death of social media”. To reconcile these, “we think about power as something that is not just top down but… emerges within kind of a Foucauldian sense in spaces of discourse and productivity”, and she closes “thinking about power as productive and then it produces worker subjectivities and responsibilities, forms of inequality, regimes of visibility, types of logics and modes of meaning making that will continue to evolve and shift”.

📚 Deeper theory

What “productive” adds (idea 7). The first half of the talk shows power as institutional: Facebook sets the rules for Zynga. The second half shows power as productive: the platform shapes the kind of worker, the way she thinks about herself, and what she counts as success. These do not conflict, but they are different kinds of explanation and they have different political answers. Institutional power suggests regulation (antitrust, interoperability). Productive power suggests cultural and organisational answers (solidarity, new norms, new ideals of work).
How the “death of social media” claim connects. If platforms are fading, does their power fade? On this view, no: the dispositif (the habits, the expectations of being visible, the entrepreneurial self) outlives any one app. That matches Nieborg’s later line that tensions remain (idea 9).
A caution on reading Foucault. “Productive power” can be used too loosely to mean “power is everywhere”, which weakens critique. The strong use ties it to specific mechanisms (metrics, norms, training) that can be traced. The book does that in the labor and metrics sections.
Reply to the “end of social media” talk. In late 2022, commentators (e.g. the “death of social media” pieces after Musk’s takeover; not searched here) predicted decline. Since then: Twitter became X; Threads and Bluesky grew; TikTok faced US legal pressure (not searched). The structure the authors describe (dependence, metrics, governance) survived each shift, which supports Nieborg’s “intensification” point.
Link to AI. Generative AI tools are being added inside platforms (auto-generated clips, AI captions, AI-written descriptions), which could deepen both institutional and productive power. See the “Current debate”.

📚 Roots: Where the traditions meet (summary table)

Question the talk asks	Tradition that answers	Key idea
Why do platforms behave this way?	Platform economics	Multi-sided markets, subsidy, openness trade-off
How do they control outsiders?	Information systems	Boundary resources
What do they do to speech and visibility?	Platform studies	Politics of platforms; threat of invisibility
Why do creators accept it?	Creative-labor studies	Aspirational labor; creative dispositif
What happens to creative work?	Metrics studies	Contingent commodity; reactivity
Is it democratic?	Democracy and inequality	Winner-take-all; algorithmic bias
How does power really work?	Foucault + institutional	Productive and institutional power together

Where others push back. Marxist and political-economy scholars (e.g. Christian Fuchs) argue that a Foucault-led view can drift away from ownership and exploitation. Others say “productive power” is hard to test. The authors’ blend answers part of this.

What they leave out. The state and law as actors, and countervailing powers (users, creators’ organising, courts), which come up only in Q&A.

Check yourself

What is the difference between institutional and productive power? Give a talk example of each.
Why does the “end of social media” claim not undo their argument?
What kind of response does each kind of power point to?

9. Q&A (1): What has changed? Sedimentation and intensification

In short. Asked what has changed since the book, Duffy says they did not predict it, or they would be as wealthy as Chamberlain. A platform is a moving target, so they tried to separate changes from continuities such as labour, power and governance. Precarity is built into these firms’ ethos, and she is interested in the extra labour needed to cope with it, such as spreading income across platforms.

🎙 In the talk. The host asks what has changed since the book and whether they predicted it. Duffy: “we did not predict them or we would all be as wealthy as Emma Chamberlain.” Any platform is “a moving target”, so they tried to separate “the changes but also the continuities”, such as labor, power, governance systems. Twitter is “especially poignant”, also for academics who find “social media’s ending… okay now what am I going to study”. Precarity is structured into the ethos of these companies… move fast and break things, and what interests her is “the additional labor it requires to reckon with such precarity”, diversifying income across platforms.

Nieborg: after 20 years studying video games, “you publish something about games and then… but what about Call of Duty part 24”. Peer review requests are “metaverses and NFTs and crypto” and “we don’t talk about that in the book that much and I think for a reason”. A reviewer said some examples are better than authors expected because “some technologies and platforms need sedimentation… time needs to pass” before high-quality scholarship exists. “We don’t talk about BeReal for obvious reasons, we don’t talk about Musk at all in the book” and would be “careful and reluctant” now, because “there is a value in the slow pace of our work”. Finally: “I don’t think the underlying tensions and the underlying shifts have dramatically changed over the last year or even two years… it’s more of an intensification, more of almost the same”. If someone disagrees “what is it that we have missed? Because then we missed a massive historical shift”.

📚 Deeper theory

Slow scholarship vs fast news. Media studies tends to lag product cycles. Two responses: chase events (fast case studies, journalism) or build concepts that travel. Nieborg and Poell choose the second. This is a methodological stance: pick structural features (multi-sidedness, boundary resources, governance) that do not depend on one app.
Sedimentation. A word from geology and sociology: layers settle and harden. Platforms’ rules, norms and user practice need time to settle before they can be studied as a stable object. The risk: by the time they settle, the object has moved. A trade-off between reliability and timeliness.
Intensification vs rupture. A standard dispute in social theory. Is a change a new epoch (rupture) or more of the same (intensification)? For platform studies see “platform capitalism” (Srnicek) as continuous with neoliberalism. The authors choose continuity for 2020–22. Their check (“tell me what we missed”) is a good habit: state what evidence would change your mind.
What happened since. After Dec 2022: X’s pay-for-reach changes; Meta’s Threads; TikTok under US pressure; large gen-AI tools; EU DSA enforcement; US court rulings on app stores. Whether these are intensification or rupture is open (see “Current debate”). Generative AI is the strongest candidate for a rupture argument, since it changes creation itself, the first of their four processes.
BeReal. A French photo app that rose in 2022 and faded. A good example of why “sedimentation” is sensible†.

Where others push back. Fast-moving fields need timely critique so that policy can react; waiting can leave policy to industry narratives. Also, “we avoid the hype” can become a refusal to face new facts. The authors’ own test is the answer: show what we missed.

What they leave out. Gen AI was not yet a mainstream topic in Dec 2022 (ChatGPT launched on 30 Nov 2022, a week earlier; from memory). The talk does not mention it. It is the main test of their “intensification” claim.

Check yourself

What does “sedimentation” mean here? What is the trade-off?
Is Nieborg claiming nothing changed? What exactly does he claim?
Name one development since 2022 that might be called a rupture, and say why.

10. Q&A (2): Governance, ethics and who is studied

In short. Asked about the ethics of platform design, Nieborg says to focus not on the end user but on how governance affects cultural producers. There is much less scholarship on how game developers, news producers and creators feel the rules, including the rules to access an API. Many media scholars have not been trained to access an API, so there is a lot we do not know.

🎙 In the talk. A student (Renan) asks about the ethics of platforms’ design to make people “indulge” in use, and who is responsible. Nieborg says his co-author Poell “has been at the heart of chapter 4 on governance”. His answer is about focus: it is important “to constantly point not so much to the end user focus… as how does this platform governance impact cultural producers”. There is “so much less scholarship” on how “game developers or news producers… creators… the workers, the media workers” are affected by “governance structures and frameworks… economically… infrastructurally… the rules to access an API”. Journalism studies “maybe” lead. Many media scholars “have not been trained” to access an API. So “there’s a lot we also do not know”.

Duffy adds that platforms set norms in “community guidelines” that are “often seen as unevenly applied and even more problematically applied in ways that disadvantage certain populations”. She cites Sophie Bishop on “brand friendliness”, so “a kind of conservative bent gets rewarded”. Creators say mainstream content “will be raised by the algorithm”, while “controversial” content or “hashtags that refer to my identity” mean being “disproportionately banned”. “Creators of color” say identity hashtags mean content “doesn’t get seen”. So the accounts “sharply defy this idea that governance is applied evenly”.

📚 Deeper theory

Engagement design and ethics. Renan’s worry is the attention economy debate (design that maximises time on app: infinite scroll, variable rewards). Tristan Harris and the “time well spent” movement; Natasha Dow Schüll, Addiction by Design (2012; from memory). In regulation, this links to EU DSA risk duties and US state laws on minors (not searched). Nieborg’s reply does not take the ethics bait directly; he turns to who is missing in the evidence.
Producer-side governance. The research gap he names is real: most work on algorithms studies consumers (filter bubbles, radicalisation, addiction). Fewer studies ask how rules of access shape suppliers. Key exceptions: Caplan and Gillespie (2020) on tiered governance and demonetisation; Duffy and Meisner (2022) on platform governance at the margins (from memory; check titles).
Brand safety. Advertisers ask platforms for “safe” content. Platforms respond by demonetising or down-ranking topics (LGBTQ, politics, sex, violence). The effect is a conservative tilt (Bishop; Caplan and Gillespie). That makes governance and money part of one system.
Why unequal enforcement is hard to prove. Platforms do not show their rules or data. Creators see only their own results. Researchers rely on interviews, “algorithmic audits” and sock-puppet accounts. The DSA data-access rules (2025) may help in the EU (see “Current debate”).
Who is responsible? Three views: (a) platform duty of care (regulation); (b) user literacy and choice; (c) collective action by workers. The talk’s Q&A gives some of (a) and (c) but does not take a stand.

Where others push back. Some say focusing on producers over end users is a political choice: harms to audiences (mis- or disinformation, addiction, mental health) may affect more people. The authors do not deny this; they pick a gap to fill.

What they leave out. Law and policy responses (Nieborg and Duffy do not mention DSA, DMA or US law in the talk). The host is a former lawyer and asked in her intro about policy, so this is a notable gap.

Check yourself

What gap in research does Nieborg point to?
What is “brand friendliness”, and how does it affect which content wins?
Why is it hard to prove that rules are applied unevenly?

11. Q&A (3): Aesthetics, games, gatekeepers, and Spotify

In short. Nieborg says industries have different standards for aesthetics, labour and creativity, so there is no one-size answer. In games, Unity and Unreal make creating easier than ever, but Apple and Google are the de facto gatekeepers of distribution. Tools are cheap, yet money still goes to the countries that have long dominated the industry. The book offers a framework to think through cases, not final answers.

🎙 In the talk. Tom Livingstone asks if aesthetic homogenisation is separate from the labor, governance and markets lens, and about Unreal Engine in filmmaking. Nieborg: “different industries have such different standards… in terms of aesthetics and labor and what we call creativity”, and it’s not a one-size-fits-all answer. For games, the book’s argument is “democratization versus concentration and then again governance”. Unity and Unreal “have made it so much easier than ever before to create video games… undeniably”, but “there are severe questions about distribution: Apple and Google have become the de facto gatekeepers” for mobile games. Tools are “virtually free or very affordable”, but “there’s massive asymmetries in who can make money”. In the game app economy, money goes to “countries that have been dominating the game industry for decades, so Western European countries, North American countries”. “You can make a game in countries that have historically been outside of the game industry but that doesn’t necessarily mean that those countries or developers… make money or are more visible on a global stage.” He admits: “we don’t necessarily always have answers”, but the book offers “a framework, a couple of steps and concepts to think through specific examples”, e.g. “game apps from Brazil”.

Then Kim Marie (the Jamaican scholar; inferred) comments from popular music: from vinyl and majors to Spotify and Apple Music, “the platform has changed and there hasn’t been much change with the political economy”; access “remains an issue”, and governance “is still the black box… we don’t know how anyone gets chosen”. She sees “a lot of continuity”.

📚 Deeper theory

Homogenisation, three possible causes. (1) Tools: shared engines and templates make results look alike (Unity/Unreal “look”). (2) Metrics: optimisation for the same signals. (3) Concentration: a few firms shape what is funded and found. Nieborg’s answer picks out the third and the distribution link in games: tools spread, money does not. Aesthetics need their own analysis (Chayka; also Hallinan and Striphas on Netflix).
Games as a platform pioneer. Games have long had closed platforms (consoles, app stores), 30% revenue cuts, and platform-set rules. Nieborg’s game-studies background (he says he has studied the game industry for 20 years) is why this field comes first in many of his examples. The mobile store’s 30% commission is the standard figure; since 2021 several legal and regulatory pushes tried to change it (see “Current debate”).
Geography. Global game revenue concentrates in a few countries (US, China, Japan, South Korea, parts of Europe). This pattern is Nieborg’s claim from his own studies; no figures were checked here. Platform visibility rules (store features, rankings) work with capital (user-acquisition spending) to keep the same winners. Cheap tools do not fix that.
Music as a parallel. Spotify Teardown (Eriksson et al., 2019) and Liz Pelly’s work on streaming payouts (from memory) show a similar black-box pattern: playlist placement decides income; rules are opaque. The reggae example matches the access ideal in the book. From the host’s own comment, the change from record labels to Spotify moved the gatekeeper, not the structure.
Unreal in film. Epic’s Unreal Engine is used for virtual production (e.g. LED walls in The Mandalorian; from memory). Tom’s point links engine power to film aesthetics, an example of infrastructure shaping style. Nieborg did not answer it directly; he returned to games.

Where others push back. Some scholars say tool democratisation does produce new aesthetics and scenes (indie games, bedroom pop, TikTok genres) and that one should not read homogenisation from concentration alone. Others suggest looking at niche communities that sit outside metrics.

What they leave out. Audience taste, genre theory and aesthetics in a direct sense. Nieborg says aesthetics are not the book’s main lens and gives structural answers instead.

Check yourself

What does Nieborg say about democratisation in games: what got easier, what did not?
Why do Apple and Google count as “gatekeepers” in mobile games?
What does the Spotify comment add to the claim that “the platform changed but not the political economy”?

12. Q&A (4): Organising — unions and hidden networks

In short. Duffy says creators have tried to organise, for example a YouTubers Union and efforts around the TikTok Creator Fund. More activity is in networks that rely on invisibility, because creators fear being demonetised if they criticise the platform they live on. Creators share pay data on crowd-sourced sites, so a brand cannot pay unequally without being seen. She calls it a different form of unionisation.

🎙 In the talk. Dennis Murphy (by email) asks whether content producers organise and whether there could be a union-like response to the imbalance of power. Duffy: “there have been various initiatives and efforts of creators to organize”, for example “YouTubers who have sought to create a YouTubers Union”, the TikTok Creator Fund and “offline efforts”. But “what is more where we’re seeing more activity is in various networks that rely upon invisibility in order to push back against platform power”, because of “this concern that… if you critique the platform on which you’ve built your livelihood they are going to punish you… by demonetizing you, kicking you off platform”. So there are “a lot of grassroots ways in which creators come together”, such as “crowd-sourced websites where creators talk about how much they’re getting compensated and their own identity characteristics”, so a brand “can’t intentionally” pay unequally, and one can see whether “a white 20-year-old woman with this audience” gets the same as “an older creator of color”. It is “a different form of unionization… we talk to each other, we share knowledge, and we create a band to support negotiations”.

📚 Deeper theory

Why standard unions are hard. Unions need a defined employer, a bargaining unit, and the power to withhold labor. Creators are “independent”, thousands of dispersed sole traders, with a platform that can cut off their income. Competition law in many countries treats collective bargaining by self-employed people as price-fixing (a debate in EU and US law; from memory). Hence hidden networks.
Real cases (from memory; check). In 2019 the German union IG Metall and YouTuber Jörg Sprave launched the FairTube campaign, which pushed YouTube to accept some talks on demonetisation transparency. The “YouTubers Union” Duffy mentions was a 2018 attempt linked to the same line. Gig workers (Uber and Deliveroo drivers) offer parallel stories, and the WGA and SAG-AFTRA strikes (2023) addressed pay and AI in film and TV.
Hidden resistance. James Scott’s “weapons of the weak” (1985) and Albert Hirschman’s Exit, Voice, and Loyalty (1970) fit: when open voice is risky and exit is costly, people use quiet, informal tactics. The crowdsourced pay sheets are information tools: they fight the information gap that platforms and brands exploit (pay transparency).
Platform cooperatives. Trebor Scholz’s “platform cooperativism” (2016) proposes worker-owned platforms. Examples are small. Duffy does not mention it.
The “invisibility” link. The earlier tension “visibility and invisibility” appears again: the strategy that protects workers is invisible organising, while the career asks for hyper-visibility. A neat reversal.
Wider organising. In many places (India, Brazil, Nigeria) creator and gig worker groups form around WhatsApp and Telegram groups. (General pattern; not checked in this talk.)

Where others push back. Labor scholars argue that informal networks cannot achieve what contracts and law do (pay floors, protection from arbitrary bans). Without legal rights, the platform keeps the upper hand. Duffy calls the result “a different form” rather than a replacement, which is cautious.

What they leave out. Legal routes (labour law, competition law, platform regulation). Results: have any networks won concessions? (FairTube is the usual example; not mentioned.)

Check yourself

Why might creators avoid open union action?
What do the crowdsourced pay sheets do, and why do they matter?
How does this answer relate to the “visibility/invisibility” tension?

Q&A

(Add questions and answers here only if worth keeping.)

About the source and how this page was made

Speaker: David Nieborg and Brooke Erin Duffy (book co-author Thomas Poell not present)

Event: Queen’s University Belfast, MA Arts Management and Cultural Policy, “Platforms and Cultural Production” in conversation (Zoom webinar)

Date: 7 Dec 2022 (from the QUB events archive page; talk itself is consistent with Nov-Dec 2022)

Length: ~58:35 (transcript ends at 58:35)

Timestamps. The transcript tool gave only two paragraph stamps. The [MM:SS] marks below were rebuilt from the caption file and are good to about ±10 seconds.

Speakers

Label Who Role
Host Maria O’Brien (says her own name) Lecturer, MA Arts Management and Cultural Policy, School of Arts, English and Languages, Queen’s University Belfast. Former lawyer; works on media industries from an Irish and European view. Chairs the event
Chat helper Kim Marie Spence (host names “my colleague Kim Marie Spence”) Runs the chat. Later makes a comment about reggae, dancehall and Spotify. The Jamaican reference suggests she is the same person (inferred; not confirmed)
Nieborg David Nieborg (introduced as “David nieborg”) Associate professor of media studies, University of Toronto; visiting professor 2022–23 at the University of Amsterdam. Speaks first (political economy, games). Joins from Amsterdam
Duffy Brooke Erin Duffy (introduced as “Brooke Aaron Duffy”; see warnings) Associate professor of communication, Cornell University. Author of (Not) Getting Paid to Do What You Love (2017). Speaks second (labor, creativity, democracy)
Absent co-author Thomas Poell First author of the book, at the University of Amsterdam. Credited; his chapter 4 on governance is named
Audience Inga Sorensen (name as captioned; spelling unsure), Renan/Yunan (an Arts Management student; spelling unsure), Tom Livingstone, Dennis Murphy (question sent by email; ex-postdoc, Trinity College Dublin, labor in film and TV) Ask about the chat, governance and ethics, aesthetics, and unions

Speaker confidence: high for Nieborg and Duffy (the host introduces them by name and role, and the speakers hand over to each other by first name). Poell does not speak.

Caption warnings.

“Brooke Aaron Duffy” = Brooke Erin Duffy. “Aaron” is a caption or reading slip.

“Mana Facebooks” = Metas / Facebook.

“Todd gillen” = Todd Gitlin (Inside Prime Time, 1983).

“Angela mcrobbie’s creativity dispotif” = Angela McRobbie’s “creative dispositif” (from Be Creative, 2016).

“fukotian” = Foucauldian.

“metaphor creators program” = most likely Meta’s creator programme, with a pun on “metaverse” (not confirmed).

“Zynga” is captioned “Zinga” or “singer” at times ( “what you saw with singer”). “Sophie Bishop” is correct. “Thomas poll” = Thomas Poell.

“Unity and unreal” = Unity and Unreal Engine (Epic Games). “be real” = BeReal.

“1.7 annually” is cut off. It probably means an estimated $1.7 million a year. The unit is missing in the captions and is not confirmed.

“unionization… Queens… Eventbrite” at the end: the recording was to go on the QUB MA’s YouTube channel.

Factual checks (done by search).

Meta layoffs. Duffy says Meta laid off “an unprecedented 13” percent. Correct: Meta announced on 9 Nov 2022 that it would cut about 11,000 jobs, about 13% of staff (Ahram/AP).

Zynga “acquired by another big game publisher”. Correct. Take-Two closed its roughly $12.7 billion purchase of Zynga on 23 May 2022 (TechCrunch).

Zynga and the “wall”. Nieborg compresses the story: Zuckerberg “said no more” and “cut the ties with that wall posting stuff”. The sources show a slower break. Facebook and Zynga revised their deal at the end of Nov 2012. Zynga stopped being required to feature Facebook ads or use Facebook Credits. Facebook could now build its own games. Players lost the ability to share game progress to the news feed from 31 Mar 2013, and Zynga’s shares fell about 13% after hours on the news (The Register, HotHardware). So the “kick” was a multi-year process, not one decision. The point he draws from it still stands.

“New to Silicon Valley”. Nieborg calls Mark Pincus “new to Silicon Valley”. From memory†: Pincus was already a known Valley founder before Zynga (e.g. Tribe.net), so “new to gaming” is the safer reading.

Emma Chamberlain and Taylor Lorenz. Duffy says Lorenz “dubbed” her “the most important YouTuber today” in 2019. A search found Lorenz’s July 2019 profile of Chamberlain (paywalled) but could not confirm the exact phrase. Treat it as Duffy’s attribution (not confirmed). The 11.9 million subscribers figure is Duffy’s own check “last night” and cannot be re-checked for Dec 2022. Wikipedia later lists about 12 million (Dec 2025) (Wikipedia).

“Chat is disabled”. Not a slip. A Zoom setting. The host jokes it is “a bit embarrassing after that talk about the complexities”.

🎙 marks what the speaker says. 📚 marks added background and the wider debate, not the speaker’s claim. † marks background from general knowledge that was not checked against a source.

Talks

Platforms and Cultural Production — David Nieborg and Brooke Erin Duffy

Summary

Map — talking points

Putting it together

Part 1 — Before you read

Key terms

People named and implied (a reading list)

The speakers’ own frame

The current debate (2022–26)

The ideas

1. The question, the scope and the four processes

📚 Roots: Political economy of media and the cultural industries

2. The Zynga story: how a platform sets the terms

📚 Roots: Platform economics — multi-sided markets and platform strategy

3. Markets, infrastructure, governance: three layers of institutional power

📚 Roots: Information systems — infrastructure and boundary resources

4. Emma Chamberlain and platform-dependent labor

📚 Roots: Creative labor, precarity and aspirational work

5. Labor: four tensions and the algorithm

📚 Roots: Platform and software studies — politics, algorithms, society

6. Creativity and the metric logic

📚 Roots: Metrics, quantification and algorithmic culture

7. Democracy, access and the “creative dispositif”

📚 Roots: Power — Foucault and the entrepreneurial self

📚 Roots: Democracy, inequality and the “democratisation” promise

8. Power as productive: the closing frame

📚 Roots: Where the traditions meet (summary table)

9. Q&A (1): What has changed? Sedimentation and intensification

10. Q&A (2): Governance, ethics and who is studied

11. Q&A (3): Aesthetics, games, gatekeepers, and Spotify

12. Q&A (4): Organising — unions and hidden networks

Q&A

Table of Contents

Label	Who	Role
Host	Maria O’Brien (says her own name)	Lecturer, MA Arts Management and Cultural Policy, School of Arts, English and Languages, Queen’s University Belfast. Former lawyer; works on media industries from an Irish and European view. Chairs the event
Chat helper	Kim Marie Spence (host names “my colleague Kim Marie Spence”)	Runs the chat. Later makes a comment about reggae, dancehall and Spotify. The Jamaican reference suggests she is the same person (inferred; not confirmed)
Nieborg	David Nieborg (introduced as “David nieborg”)	Associate professor of media studies, University of Toronto; visiting professor 2022–23 at the University of Amsterdam. Speaks first (political economy, games). Joins from Amsterdam
Duffy	Brooke Erin Duffy (introduced as “Brooke Aaron Duffy”; see warnings)	Associate professor of communication, Cornell University. Author of (Not) Getting Paid to Do What You Love (2017). Speaks second (labor, creativity, democracy)
Absent co-author	Thomas Poell	First author of the book, at the University of Amsterdam. Credited; his chapter 4 on governance is named
Audience	Inga Sorensen (name as captioned; spelling unsure), Renan/Yunan (an Arts Management student; spelling unsure), Tom Livingstone, Dennis Murphy (question sent by email; ex-postdoc, Trinity College Dublin, labor in film and TV)	Ask about the chat, governance and ethics, aesthetics, and unions