Data-Driven Governance Lecture Quiz

Public Law 2 - Lecture 3: Data, Indicators and Rankings

• Lecture overview: Data, indicators, and rankings in public law, specifically relating these methodologies to governance.
• Lecture 3 topics:
  • How data functions as a tool within neoliberal governance.
  • Definitions and characteristics of indicators.
  • Examination of examples, including World Bank's Business Enabling Environment and university league tables.
• Quick recap (Lectures 1 & 2):
  • Sovereignty beyond the state (e.g., regulatory state, global governance networks).
  • Erosion and transformation of sovereignty.
  • Neoliberalism and globalization.
  • Conceptual understanding of these changes (Foucault's governmentality lens).
• Lecture 3 content:
  • Rise in quantification and commodification.
  • Data as constructs (epistemic categories) shaping understandings of the world (i.e. how our knowledge of the world is affected.)
• Lecture 4: Focuses on governance through data and surveillance.
• Specific indicators discussion within lecture 3:
  • Establishing how data operates in neoliberal governance.
  • Explaining/detailing the process of quantification, mathematization, and comparison through data.
  • Defining and outlining the characteristics of indicators.
  • Analyzing how indicators function using the World Bank's Business Enabling Environment and university league tables as examples.
• Key take aways:
  • Quantification in data is reductive (losing nuance).
  • "What gets counted gets done" (indicators drive value and resource allocation).
  • Rankings and indicators are subject to manipulation ("gamed").
  • Rankings and indicators influence prioritization and change the priorities of those being measured (the importance of incentives).
• Data as a neoliberal technology of governance:
  • Data's function in persuasion/education/informative purposes.
  • Data's impact on quantifying and comparing social phenomena.
  • Transformation, by data, of social processes and objects to commodities. Social phenomena as quantified "facts."
  • Influence, via data, on epistemic categories and understandings of the world. Impact on ways we perceive, construct, the world, and what values are. Example of the use of this approach in a specific experiment.
• Defining "data":
  • Information collected, processed, and retained by governments, companies, and other sectors.
  • Not a new phenomenon; early forms of centralized data collection and analysis existed. Shift towards rule-governed processes with targeted outcomes.
• Data as a tool of regulation:
  • Educating, informing, and persuading.
  • How does data create soft power? Examples to discuss: Soft power, "docile bodies," self-regulation, processing and analyzing data for policy making, and epistemic categories within which we think about value.
• What are Indicators? (key elements):
  • Calculative technique, based on numerical and organizational ranking systems, part of New Managerialism.
  • A purposive tool to change and influence Organizational behavior. This is how they shape decision-making.
  • Simplification, de-contextualisation, and reduction of complex issues to selected data, to measure or rank.
  • Used to establish hierarchies. The comparison, evaluation, and hierarchy aspects of indicators, according to Davis, et al, are purposefully done.
  • Placeholders for and/or markers for policy ideas.
  • Named collections of data that purport to represent past or future performance of units.
• Key characteristics of indicators:
  • Significance of the indicator and associated claims of power to define and represent things, such as "rule of law".
  • Standardized ordinal structure for comparison and ranking, with pressure for "improvement."
  • Simplifying complex phenomena, and potential for use in evaluation.
• Indicators as calculative techniques:
  • Offering quantitative accountability through outputs, tables, targets, and rankings.
  • Enabling auditing and accountability in almost all areas of life (transparency, legitimacy, reliability, authority, and unassailability).
• Characteristics of indicators (cont.):
  • Simplifying and de-contextualizing data (supplanting local cultures with rational methods).
  • Evaluative (quantifying and comparing based on conceptual and normative tools).
  • Establishing hierarchies based on relational position within units/etc. The relational positions that indicators create.
  • Apparent objectivity and scientific nature, yet with hidden value judgements (decisions about what gets counted, when, how, by whom, how data is presented and analysed (which affects what results, and in what ways.)/
• Data as incomplete and partial:
  • Data collection may produce incomplete/partial measures of certain things (example of the violence against women reports).
• Case study 1: Quantifying and comparing legal systems:
  • The reason behind counting legal systems (ideal investment climate belief, market-based technologies).
• Case study 2: University league tables:
  • Quantifying, comparing, and ranking higher education. Use of indicators to shape/influence Organizational behavior.
  • The potential influence and effects of these types of rankings on institutions (incentives, ranked entities, "numbers game", pressure) and actors.
• Thought experiment: creating a university ranking:
  • What variables to consider and measure?
  • How would these variables be measured?
• Measuring the quality of education (OfS):
  • Assessing quality through independent external experts and including, data from academics and students
  • Importance of breaking down quality into multiple sub-indicators
• University league tables as rankings:
  • Recording objective/subjective data. Potential for bias (natural biases).
  • Impacts of what isn't measured.
  • Effects/influence of rankings on different actors/entities involved (students, universities, and regulators). Also focusing on "gaming the system."
• What's next:
  • Upcoming lectures on regulation by data and surveillance. Seminar 2 on technologies of governance, and university league tables.
  • Assessment 1 deadline.