Traditional media and the new media

Paper 4 – Media: Ownership and Control

1. Objective

Analyse how ownership and control shape the production, distribution and consumption of media, compare traditional (pre‑digital) media with new (digital) media, and evaluate their impact on culture, politics and society – as required by the Cambridge AS & A Level Sociology (9699) Paper 4 syllabus.

2. Traditional Media

Established mass‑communication channels that pre‑date the internet.

2.1 Main Forms

• Print – newspapers, magazines, journals
• Broadcast – television, radio
• Film – cinema, home video

2.2 Ownership Structures

• Large private corporations (e.g., News Corp, Disney)
• State‑owned broadcasters (e.g., BBC, CCTV)
• Family‑run conglomerates (e.g., Murdoch family)
• Cross‑ownership arrangements (e.g., a company owning both a newspaper and a TV channel)

2.3 Control Mechanisms

• Editorial policies – set by senior editors, owners or board of directors
• Regulatory bodies – Ofcom, FCC, etc., issue licences and enforce content standards
• Advertising revenue – influences programme selection and news agenda
• Political pressure – through ownership ties, state funding or direct government directives

2.4 Key Theoretical Perspectives (with brief critical evaluation)

• Political Economy – emphasises profit motives and concentration of ownership.
  • Strengths: Highlights power relations and commercial imperatives.
  • Limitations: Can under‑estimate audience agency and cultural meanings.
• Propaganda Model (Herman & Chomsky, 1988) – five filters: ownership, advertising, sourcing, flak, anti‑communism.
  • Strengths: Provides a clear framework for analysing bias.
  • Limitations: Developed for US news; may not fit all media systems or the interactive nature of digital media.
• Cultural Imperialism – dominance of Western media content worldwide.
  • Strengths: Explains global flow of media products.
  • Limitations: Overlooks hybridisation and local reinterpretations.
• Ownership Concentration Metrics – e.g., Herfindahl‑Hirschman Index (HHI) to measure market share.
  • HHI = ∑(market‑share²); values above 2 500 indicate high concentration.
  • Useful for comparing levels of concentration across countries.

3. New Media (Digital Media)

Internet‑based platforms that enable interactive, user‑generated content.

3.1 Main Forms

• Social networking sites (Facebook, Twitter, TikTok)
• Online news portals and blogs
• Streaming services (Netflix, YouTube, Disney+)
• Podcasts and digital radio
• Peer‑to‑peer and blockchain‑based platforms

3.2 Ownership Structures

• Tech conglomerates (Alphabet, Meta, Amazon)
• Start‑up platforms funded by venture capital
• Decentralised models – peer‑to‑peer networks, blockchain‑based services
• Hybrid models – public‑private partnerships (e.g., BBC iPlayer)
• Cross‑ownership in the digital sphere (e.g., a firm owning a streaming service and an advertising network)

3.3 Control Mechanisms

• Algorithmic curation – proprietary code decides what users see (recommendation engines, news‑feed ranking).
• Platform policies – community standards, terms of service, moderation practices.
• Data monetisation – user data sold to advertisers; influences content exposure.
• Network effects – dominant platforms become de‑facto gatekeepers.
• Regulatory challenges – cross‑border jurisdiction, GDPR, Digital Services Act (EU), Online Safety Bill (UK).

3.4 Key Theoretical Perspectives (with brief critical evaluation)

• Network Society (Castells, 1996) – the internet as a structural platform for power.
  • Strengths: Highlights the importance of networked communication for social change.
  • Limitations: May over‑emphasise the uniformity of the network and under‑play digital divides.
• Digital Divide – unequal access to technology shapes participation.
  • Strengths: Draws attention to socioeconomic and geographic inequalities.
  • Limitations: The concept can be too broad; needs disaggregation (access, skills, usage).
• Surveillance Capitalism (Zuboff, 2019) – extraction of behavioural data for profit.
  • Strengths: Links data practices to power and autonomy.
  • Limitations: Focuses mainly on US tech giants; less applicable to state‑run platforms.
• Participatory Culture (Jenkins, 2006) – audiences as producers (prosumer model).
  • Strengths: Recognises creative agency of users.
  • Limitations: Not all users have equal capacity to produce; platform algorithms still shape visibility.

4. Media & Globalisation

Ownership and control operate on a trans‑national scale, shaping the flow of culture, information and capital.

• Multinational tech firms (e.g., TikTok, Netflix) export algorithms and content formats worldwide, creating a “global media flow”.
• Trans‑national ownership can reinforce cultural imperialism but also enable hybrid cultural products (e.g., Korean pop music on YouTube).
• Regulatory responses differ: the EU’s Digital Services Act seeks to curb the power of non‑European platforms, whereas China’s Great Firewall blocks foreign services and promotes domestic ownership.

5. Media & Religion

Ownership influences religious discourse and the visibility of faith‑based content.

• Televangelist networks (e.g., Trinity Broadcasting Network) are privately owned and fund‑raised through viewer donations, shaping evangelical agendas.
• Public broadcasters often allocate specific slots for religious programming (e.g., BBC’s “Songs of Praise”).
• On digital platforms, YouTube and Instagram enable independent religious creators, but algorithmic recommendation can amplify sensationalist or extremist content.

6. Media‑Effects Theories (Syllabus Requirement)

These models explain how media content influences audiences and link directly to ownership and control.

Theory	Core Proposition	Key Study / Author	Relevance to Ownership/Control	Critical Evaluation
Agenda‑setting	Media determine “what” issues the public thinks about.	McCombs & Shaw (1972)	Editorial choices (traditional) or algorithmic ranking (new) shape the public agenda.	Strong empirical support for “first‑level” agenda‑setting; less clear for “second‑level” (attribute) effects in fragmented digital environments.
Framing	Media influence “how” issues are interpreted.	Entman (1993)	Ownership bias or platform design (headline styles, thumbnail images) frames audience perception.	Effective for analysing media texts, but framing can be contested by user‑generated counter‑frames.
Cultivation	Long‑term exposure to media shapes perceptions of social reality.	Gerbner et al. (1994)	Concentrated ownership can produce a homogenised worldview; personalised feeds intensify niche “cultivation”.	Evidence strongest for TV; mixed findings for algorithmic feeds where exposure is highly selective.
Uses‑and‑Gratifications	Audiences actively select media to satisfy needs (information, entertainment, social interaction).	Katz, Blumler & Gurevitch (1974)	Choice mediated by platform algorithms, pay‑walls and subscription models.	Highlights agency, but can under‑play structural constraints such as algorithmic nudging.
Spiral of Silence	People conceal opinions they think are in the minority.	Noelle‑Neumann (1974)	Dominant viewpoints amplified by editorial line or echo‑chamber algorithms.	Empirical support varies; digital anonymity can both silence and empower minority voices.
Cultural Studies (Hall)	Audiences decode media texts in varied ways based on social position.	Stuart Hall (1973)	Ownership influences dominant codes; digital interactivity creates new sites of resistance and reinterpretation.	Provides a nuanced, qualitative lens but can be difficult to operationalise in quantitative assessments.

7. Comparative Overview

Aspect	Traditional Media	New Media
Primary Channels	Print, broadcast, film	Websites, apps, streaming platforms
Ownership	Few large corporations or state bodies; often cross‑ownership within national markets	Tech giants, venture‑capital start‑ups, decentralised networks; increasingly trans‑national
Control of Content	Editorial boards, regulators, advertisers	Algorithms, platform policies, data‑driven advertising, network effects
Audience Role	Predominantly passive consumers	Active participants – comment, share, remix, create
Revenue Model	Advertising, subscription, licence fees, state funding	Targeted ads, subscription, data monetisation, micro‑transactions, freemium models
Regulatory Landscape	Well‑established national bodies (Ofcom, FCC)	Emerging trans‑national frameworks (EU Digital Services Act, UK Online Safety Bill) plus self‑regulation
Key Theoretical Lens	Political Economy, Propaganda Model, Cultural Imperialism	Network Society, Surveillance Capitalism, Participatory Culture

8. Regulatory Landscape – Traditional vs. Digital

9. Digital Divide & Access Inequality

The digital divide refers to gaps in:

• Physical access – broadband availability, device ownership.
• Skills – digital literacy, ability to evaluate online information.
• Usage patterns – frequency, purpose (e.g., education vs. entertainment).

Research (Pew Research Centre 2023) shows that 23 % of adults in low‑income households lack reliable internet, limiting participation in digital news and civic engagement. The divide reinforces existing social inequalities and shapes who can influence or resist dominant media narratives.

10. Ownership Concentration & Cross‑Ownership

Measuring concentration helps assess the power of media owners.

• Herfindahl‑Hirschman Index (HHI) – sum of squared market‑share percentages; values > 2 500 indicate high concentration.
• Cross‑ownership – a single entity owning multiple media types (e.g., newspaper + TV + online platform) can limit pluralism.
• Examples: Sinclair Broadcast Group’s ownership of numerous US TV stations; Disney’s control of film studios, TV networks and streaming services (Disney+).

11. Behavioural & Societal Impacts of New Media

• Political participation – social media can mobilise protests (e.g., Arab Spring) but also spread misinformation and “fake news”.
• Consumer behaviour – personalised recommendations drive impulse purchases and brand loyalty.
• Health attitudes – exposure to health misinformation (e.g., vaccine myths) influences public‑health outcomes.
• Public discourse – algorithmic echo chambers may reinforce polarisation; niche communities can give voice to marginal groups.
• Democratic engagement – citizen journalism expands the news agenda, yet platform moderation can limit controversial speech.

Recent data (Reuters Institute Digital News Report 2024) indicate that 68 % of adults now obtain news primarily online, underscoring the need to assess these behavioural effects.

12. Media Representations

Ownership and control affect how different social groups are portrayed.

• Class – reality TV such as “Love Island” often depicts working‑class participants as frivolous, reinforcing stereotypes; BBC documentaries tend to provide more nuanced class analysis.
• Gender – television advertising continues to use gendered roles (women in cleaning products, men in cars); YouTube creators can subvert these norms, yet algorithmic recommendations may still prioritise gender‑stereotyped content.
• Ethnicity – streaming series like “Master of None” showcase diverse narratives, whereas traditional prime‑time TV in many countries remains dominated by white protagonists.
• Age – news coverage often marginalises older adults, focusing on youth culture; TikTok’s “#Boomer” trend both mocks and gives visibility to older users.
• Religion – televangelist networks foreground evangelical perspectives; algorithmic feeds can amplify sensationalist religious content while marginalising minority faiths.

13. Implications for Society

1. Agenda‑setting power – both forms shape public discourse; digital algorithms add a personalised layer.
2. Concentration of ownership – risk of homogenised viewpoints; new media concentrates power in a handful of tech firms.
3. Democratic participation – digital platforms broaden citizen journalism but also facilitate misinformation.
4. Privacy and surveillance – extensive data collection influences content exposure and behavioural targeting.
5. Cultural representation – traditional media often mirrors dominant cultures; new media can amplify marginal voices, yet platform bias may reproduce existing inequalities.
6. Regulatory tension – national regulators struggle to control trans‑national platforms, leading to fragmented governance.

14. Case Studies

• BBC vs. Netflix – public‑service remit and licence‑fee funding versus global profit‑driven streaming model.
• Fox News ownership & political influence compared with Facebook’s role in political advertising and algorithmic news‑feed curation.
• China’s state‑controlled CCTV contrasted with the Great Firewall that regulates internet content and blocks foreign platforms.
• TikTok’s algorithmic export of trends – illustrates media‑globalisation and the power of a single platform to shape worldwide youth culture.

15. Summary

Ownership and control determine what information reaches the public and how it is interpreted. Traditional media features relatively clear regulatory frameworks and static ownership structures, whereas new media introduces algorithmic control, data‑driven economics and trans‑national corporate power. Understanding these dynamics – through the lens of political‑economy, propaganda, network society, surveillance capitalism and media‑effects theories – is essential for analysing media influence on culture, politics and society within the Cambridge AS & A Level Sociology (9699) syllabus.