Klausur essay question example

What can states do to prevent or reduce political violence? Describe several options and discuss advantages and disadvantages.

Key concepts (1)

• political violence - the use of force by a person or group with a political motivation/purpose
  • e.g., assault, robbery, rioting, insurgency, assassination, terrorism, rebellion, guerrilla warfare and civil war, revolution
  • can be differentiated by nature of the objectives, the targets of attacks, the organisational structure of groups, and by the repertoire of actions

Key concepts (2) - causes of PV activity

1. broad environment/contextual factors (macro-level)
   • preconditions: factors that set the stage for PV over the long run
   • precipitants: specific events that immediately precede the occurrence of PV
2. circumstances and actors (meso-level)
   • PV as part of ‘strategy’ (for certain goals) and may be ‘rational’
3. psychological variables that encourage or inhibit (micro-level)
   • ego-defensive needs, cognitive processes, socialization — but also normality
   • evolving dynamics of commitment, risk, solidarity, loyalty, guilt, revenge, isolation

Key concepts (3)

• radicalisation (attitudinal) - social and psychological process of increased commitment to extremist political or religious ideology
  • mirrored by deradicalisation
  • cognitive alignment - recognition of some conditions as wrong \(\rightarrow\) framing of those conditions as unjust and violence as just \(\rightarrow\) singling out of specific responsibilities, and the demonisation of the other
• engagement (behavioural) - participation in politically violent activity
  • mirrored by disengagement

Key concepts (4)

• strategy - a combination of a claim (or demand), a tactic, and a site (or venue); alternatively, consisting of 3 elements:
  1. Targeting - who/what is being acted upon by tactics
  2. Tactics - types of collective action and manner of their performance
  3. Timing - some moments present greater opportunity than others

Key concepts (5)

• radical subcultures - a cultural group within a larger culture with its own traits, beliefs, and interests, typically distinct from and sometimes at odds with the larger culture
• leadership - Weber’s 3 ideal types: legal, traditional, charismatic
  • leadership tasks (Earl 2007)

Key concepts (6)

• foreign fighters - individuals who travel to a conflict zone from another territory (prima facie evidence of radicalism \(\rightarrow\) engagement in political violence; a ‘security failure’ by authority of origin state?)
  • motivations: ideology, benefits, interpersonal connections, etc.
  • state response options: praise/support, ignore/disregard, programmatic intervention, criminal justice intervention, forceful intervention

Key concepts (7)

• electoral violence - coercion directed towards actors and/or objects during the electoral cycle … part of a menu of electoral manipulation
  • intra-systemic violence - “try to win under the existing system”; “suppress or drown out the voices of political opponents”
  • anti-systemic violence - “depress participation as much as possible in order to undermine the legitimacy of the election”

Key concepts (8)

• escalation: a rise in the frequency and/or severity of violent actions
  • framing logics, strategic logics, organisational logics, constituency/social logics
• restraint: a deliberate restriction (either reducing or completely stopping) of violent actions
  • strategic logics, moral logics, logic of ego maintenance, logic of outgroup definition, organisational logic
• dimensions of repression/social control - identity of repressive agent, character of repressive action, whether repressive action is observable
  • many repressive options…

Notable research findings (1), by class number

–2. (a) economic factors are not reliable predictors of terrorist activity; (b) social factors help drive right-wing terrorism (Piazza 2017)

–3. (a) paths of radicalisation: ideological, instrumental, solidaristic - (della Porta 2018; Bosi and Porta 2012); (b) 5 barriers to mass violence: i. viewed as counterproductive, ii. preference for interpersonal violence, iii. changes in focus availability, iv. internal org. conflict, v. moral apprehension (Simi and Windisch 2020)

–5. post-conflict radical milieu can be key factor in mobilising for political violence (Metodieva 2022)

–7. common profile of ISIS foreign fighters: male, well-educated, urban, unmarried, and young (Morris 2023)

Notable research findings (2), by class number

–8. violence decreases turnout but that the effect is larger for anti-systemic violence; intra-systemic violence appears intended to selectively depress turnout among opposition supporters (Harbers, Richetta, and van Wingerden 2022); non-violent more than twice as likely to achieve full or partial success compared to violent cases (Chenoweth and Stephan 2011), nonviolent campaigns are better at eliciting broad and diverse support, nonviolent campaigns create more defections among the opposition, nonviolent campaigns have a broader set of tactics at their disposal, nonviolent campaigns often maintain discipline even in the face of escalating oppression; violence complementing already and continuing high mobilisation is effective in making regime more sensitive to protest costs (Kudelia 2018)

Notable research findings (3), by class number

–10. people may shift their attitudes about political violence… when a different movement poses a new situational variation (Setter and Nepstad 2022); extremists (esp. Islamists) gain more discursive space after attacks, politicians from right-wing parties were more visible than politicians from left-wing parties in political debates after extreme right and Islamist attacks, the content of public debates after terrorist attacks was related to the ideological motive behind the attack, Terrorist attacks reduce the public legitimacy of extremist actors and their political agenda in public debates, legitimacy of Islam decreases to a greater extent after Islamist attacks than the legitimacy of nationalism does after extreme right attacks (issues) (Völker 2023)

Notable research findings (4), by class number

–12. bans: attitude towards violence not a clearly important factor, two key conditions: veto player agreement and (especially) securitization (Bourne and Veugelers 2022); bans can be motivated by social pressure mechanisms, (specific) visibility is important for bans, German government applies instrumental logic rather than legal logic in banning decisions

Tips for preparing for Klausur

Tips for preparing for Klausur

Starting questions

Common uses of online tools by extremists

Common uses of online tools by extremists

Common uses of online tools by extremists

Common uses of online tools by extremists

Common uses of online tools by extremists

Common uses of online tools by extremists

Extremist uses of online tools - agitprop

Common uses of online tools by extremists

Extremist uses of online tools - recruitment

Common uses of online tools by extremists

Extremist uses of online tools - coordinating

Common uses of online tools by extremists

Extremist uses of online tools - training

Common uses of online tools by extremists

Extremist uses of online tools - financing

Extremist uses of online tools - financing

Extremist uses of online tools - financing

Extremist uses of online tools - financing

Extremist uses of online tools - financing

Common uses of online tools by extremists

Models of ‘counterspeech’ - Saltman, Kooti, and Vockery (2021)

RQs:

Beyond measuring the basic metrics of reach and engagement, can [online intervention programmes] show behavioral change and/or sentiment shift in the intended target audience exposed to this content? Could exposure to counterspeech in at-risk or radicalized audiences perhaps have the unintended consequence of further radicalization, or act as a catalyst to the radicalization process? How best can private tech companies work with non-governmental organizations (NGOs) and experts in the PVE/ CVE space?

FB’s P/CVE concept - (Saltman, Kooti, and Vockery 2021)

two counterspeech modes to test - (2021)

two counterspeech modes to test - (2021)

findings - (Saltman, Kooti, and Vockery 2021)

1. no evidence that counterspeech does harm
2. A/B test: among highest risk group, decreased engagement with violent extremist content observed
3. focusing on behavioural signals to define an at-risk audience is helpful
4. single, isolated signals of one shared piece of violent extremist content are misleading indicators of individual attitudes
5. counterspeech videos must be short and clear
6. Redirect Initiative (intervening on passive content searches) model yields increases in engagement with online resources and off-line practitioners and resources

Multi-platform activity (Mitts 2025) - regulation challenges

• assumption: stronger action by platform companies will decrease their ability to exploit the internet
  • this assumption is plausible in isolated platform perspective—less so in multi-platform perspective
  • platforms largely moderate content in isolation, but extremist actors coordinate activity across multiple platforms
• adaptation mechanisms:
  • platform migration: move to alternative platforms
  • messaging: moderate discourse on regulated platforms
  • mobilisation: problematise platforms’ content moderation policies/practices

Regulation approaches (Gorwa 2024)

• contest
• collaborate
• convince

Regulation approaches (Gorwa 2024)

• collaborate
• convince

• legally binding, enforceable rules
  • executive orders; legislatures pass laws (e.g., data protection, competition regulation, consumer safety; cybersecurity)

Regulation approaches (Gorwa 2024)

• contest
• collaborate
• convince

Regulation approaches (Gorwa 2024)

• contest
• convince

• non-binding, voluntarily enacted rules designed with government input, occasionally featuring binding procedural constraints
  • may be agreed by a mix of industry, firm, and civil society stakeholders → implemented voluntarily by industry

Regulation approaches (Gorwa 2024)

• contest
• collaborate
• convince

Regulation approaches (Gorwa 2024)

• contest
• collaborate

• using existing channels to raise grievances rather than striving for new rules
  • often occurs in the shadows, few public-facing elements
  • ‘cheap’ to pursue and implement → but also ‘cheap’ consequences (no binding sanctions, probably least impactful)

Regulation approaches (Gorwa 2024)

• contest - legally binding, enforceable rules
• collaborate - non-binding, voluntarily enacted rules designed with government input, occasionally featuring binding procedural constraints
• convince - using existing channels to raise grievances rather than striving for new rules

Major extant regulation, forums, etc. (cf. Gorwa 2024; Conway et al. 2023)

• Germany’s ‘Network Enforcement Law’ (NetzDG)
• France’s Avia Law (declared unconstitutional and revised drastically)
• EU’s Digital Services Act (DSA)
• Terrorist Content Online (TCO) Regulation
• Christchurch Call
• European Union Internet Forum (EUIF)
• Global Internet Forum for Countering Terrorism (GIFCT)
  • hash-sharing database
• Tech Against Terrorism

‘dangerous actors’ on Meta (Biddle 2021)

Extreme right, Islamist, Drug cartel, Extreme left, Buddhist nationalist, Separatist

CasaPound v. Facebook (e.g., Golia and Behring 2020)

• CasaPound (e.g., Froio et al. 2020): (neo-)‘fascist’ organisation in Italy, highly active on digital media

• 9.9.2019: Facebook deactivates CasaPound page (and representatives), arguing the content is ‘hate speech’ and ‘incitement to violence’, violating Facebook’s Terms of Use

• CP argues (before Court of Rome) ‘it proposed an update of historical fascism that exclusively values its social policies, and that it has publicly condemned racial laws’; that it does not violate Facebook’s terms of service — and that CP protected by article 21 of the Italian constitution

• see further at: https://globalfreedomofexpression.columbia.edu/cases/casapound-v-facebook/

md`## Poll results (Respondents: ${respondentCount}) and CasaPound v. Facebook`

• what is at stake here? who decides? who ought to?

import { liveGoogleSheet } from "@jimjamslam/live-google-sheet";
import { aq, op } from "@uwdata/arquero";

// UPDATE THE LINK FOR A NEW POLL
surveyResults = liveGoogleSheet(
  "https://docs.google.com/spreadsheets/d/e/" +
    "2PACX-1vRCCNFiUVI8VclRPb-6-teUiMvqZyDKKGIeCZOQYU7JhYwrLPBPKH337eqnrb6YiaVzCSraYw7CeRBC/" +
    "pub?gid=920297838&single=true&output=csv",
  10000, 1, 6); // adjust the last number to select all relevant columns 

respondentCount = surveyResults.length;

defineCounts = aq.from(surveyResults)
  .select("define")
  .groupby("define")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
define_maxCountRE = Math.max(...defineCounts.objects().map(d => d.count));

plot_define = Plot.plot({
  marks: [
    Plot.barY(defineCounts, {
      x: "define",
      y: "count",
      fill: "define",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "state actors",
      "platform companies",
      "independent regulator",
      "other"
    ],
    range: [
      "teal",
      "indigo",
      "forestgreen",
      "violet"
    ]
  },
  marginBottom: 200,
  x: { label: "", tickSize: 2, tickRotate: -30, padding: 0.2,
    domain: ["state actors", "platform companies", "independent regulator", "other"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(defineCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, define_maxCountRE]
  },
  facet: { data: defineCounts, x: "measure", label: "" },
  marginLeft: 80,
  style: {
    width: 1600,
    height: 500,
    fontSize: 40,
  },
});

policyCounts = aq.from(surveyResults)
  .select("policy")
  .groupby("policy")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
policy_maxCountRE = Math.max(...policyCounts.objects().map(d => d.count));

plot_policy = Plot.plot({
  marks: [
    Plot.barY(policyCounts, {
      x: "policy",
      y: "count",
      fill: "policy",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "state actors",
      "platform companies",
      "independent regulator",
      "other"
    ],
    range: [
      "teal",
      "indigo",
      "forestgreen",
      "violet"
    ]
  },
  marginBottom: 200,
  x: { label: "", tickSize: 2, tickRotate: -30, padding: 0.2,
    domain: ["state actors", "platform companies", "independent regulator", "other"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(policyCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, policy_maxCountRE]
  },
  facet: { data: policyCounts, x: "measure", label: "" },
  marginLeft: 80,
  style: {
    width: 1600,
    height: 500,
    fontSize: 40,
  },
});

CasaPound v. Facebook (e.g., Golia and Behring 2020)

• Court decision:
  • ‘Facebook holds a special position and its mission aims to uphold freedom of expression’
  • CP page deactivation violated its rights as a political party (under article 49 of the Constitution)
  • ordered FB to reactivate page(s) and pay a penalty of 800 EUR for each day of deactivation

CasaPound v. Facebook (e.g., Golia and Behring 2020)

• Facebook appealed (unsuccessfully), saying it is ‘a private company operating for profit protected by art. 41 of the Constitution’, that:

the order had erroneously attributed a special nature to the contract between the social network and the user, when it was instead an ordinary contract under civil law. In the absence of any legal basis, according to Facebook, it is not possible to attribute public service obligations to private sector players such as the protection of freedom of association and expression. Likewise, Facebook argued that it is not required to ensure special protection to some users such as organizations engaged in political activities by virtue of their role in the political debate.

Predominant approach and deplatforming

approachCounts = aq.from(surveyResults)
  .select("approach")
  .groupby("approach")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
approach_maxCountRE = Math.max(...approachCounts.objects().map(d => d.count));

plot_approach = Plot.plot({
  marks: [
    Plot.barY(approachCounts, {
      x: "approach",
      y: "count",
      fill: "approach",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "do nothing",
      "attach warning",
      "reduce possible views",
      "permanently remove post",
      "suspend poster's account"
    ],
    range: [
      "teal",
      "goldenrod",
      "darkorange",
      "darkolivegreen",
      "darkred"
    ]
  },
  marginBottom: 260,
  x: { label: "", tickSize: 2, tickRotate: -30, padding: 0.2,
    domain: ["do nothing", "attach warning", "reduce possible views", "permanently remove post", "suspend poster's account"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(approachCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, approach_maxCountRE]
  },
  facet: { data: approachCounts, x: "measure", label: "" },
  marginLeft: 80,
  style: {
    width: 1600,
    height: 500,
    fontSize: 40,
  },
});

deplatformingCounts = aq.from(surveyResults)
  .select("deplatforming")
  .groupby("deplatforming")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
deplatforming_maxCountRE = Math.max(...deplatformingCounts.objects().map(d => d.count));

plot_deplatforming = Plot.plot({
  marks: [
    Plot.barY(deplatformingCounts, {
      x: "deplatforming",
      y: "count",
      fill: "deplatforming",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Strongly disagree",
      "Disagree",
      "Neutral",
      "Agree",
      "Strongly agree"
    ],
    range: [
      "red",
      "pink",
      "lightgrey",
      "lightgreen",
      "forestgreen"
    ]
  },
  marginBottom: 180,
  x: { label: "", tickSize: 2, tickRotate: -45,
    domain: ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(deplatformingCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, deplatforming_maxCountRE]
  },
  facet: { data: deplatformingCounts, x: "measure", label: "" },
  marginLeft: 140,
  style: {
    width: 1350,
    height: 500,
    fontSize: 30,
  }
});

Deplatforming effects

• diminishing the scale of influence (Ghaffary 2022)
  • Facebook, Youtube: billions of users
  • Parler, Gettr (e.g.): at most a few million users
  • Telegram: a few hundred million users, little regulation
    • e.g., Proud Boys’ use (Bailard et al. 2024)
    • more emphasis on content moderation after CEO’s arrest in 2024 …

Deplatforming effects (Thomas and Wahedi 2023)

• RQ: How does removing the leadership of online hate organisations from online platforms change behaviour in their target audience?
• cases: six network disruptions (i.e., deplatforming) on Facebook
  • NB: the researchers are/were Meta employees
• finding: network disruptions reduced the consumption and production of hateful content

The results suggest that strategies of targeted removals, such as leadership removal and network degradation efforts, can reduce the ability of hate organizations to successfully operate online.

• BUT, finding comes from looking at one platform in isolation

Deplatforming effects (Chandrasekharan et al. 2017)

• 10 June 2015, Reddit banned several subreddits, including: r/fatpeoplehate and r/CoonTown
• RQ1: What effect did Reddit’s ban have on the contributors to banned subreddits?
• RQ2: What effect did the ban have on subreddits that saw an influx of banned subreddit users?
• findings:
  • many users from banned subreddits became inactive
    • led to a drop in Reddit users (some migrated to other platforms)… what’s the significance of this finding?
  • volume of active users’ posting mostly unchanged
  • a dramatic decrease in hate speech usage by the treatment users post-ban

Content moderation, deplatforming legitimacy (Pradel et al. 2024)

• key concept: Toxic speech as consisting of…
  1. incivility,
  2. intolerance, and
  3. violent threats
• experimental design: randomly exposed people (in U.S.) to toxic speech social media posts → effect on users’ content moderation preferences

Moderation, deplatforming legitimacy (Pradel et al. 2024)

Moderation, deplatforming legitimacy (Pradel et al. 2024)

A coda: disinformation culpability

Should criminal penalties exist for spreading disinformation?

disinformationCounts = aq.from(surveyResults)
  .select("disinformation")
  .groupby("disinformation")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
disinformation_maxCountRE = Math.max(...disinformationCounts.objects().map(d => d.count));

plot_disinformation = Plot.plot({
  marks: [
    Plot.barY(disinformationCounts, {
      x: "disinformation",
      y: "count",
      fill: "disinformation",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Yes",
      "No",
      "Maybe"
    ],
    range: [
      "forestgreen",
      "darkred",
      "goldenrod"
    ]
  },
  marginBottom: 80,
  x: { label: "", tickSize: 2, tickRotate: -1, padding: 0.2,
    domain: ["Yes", "No", "Maybe"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(disinformationCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, disinformation_maxCountRE]
  },
  facet: { data: disinformationCounts, x: "measure", label: "" },
  marginLeft: 60,
  style: {
    width: 1600,
    height: 500,
    fontSize: 40,
  },
});