Critical realism

Ontology

  • Thought operations - actions to “arrive from knowledge of one thing to knowledge of something else”
  • Law - mechanism existing in reality whose observable effects vary; “tendency”
  • Universal concepts (“universalia”) - concepts implying generalization
    • empirical categories (sharing formal property) vs abstract concepts (universal in the sense of “constituent”)
  • Structure, mechanisms, transfactuality - a bit similar to metaphysics?
    • Sayer - “nature’s uniformity – to which many scientists have appealed – derives not from the “accidental” regularities of sequences of contingently related things but from the internal relations, structures and ways-of-acting of things themselves.”
  • Emergent powers? Stratum?

Epistemology

  • Reasoning as precondition for knowledge Incl. feeling, intuition, imagination, creativity? “Reality does not speak for itself”.

Methodology

Goals

  • Explain events and processes
    • “To explain something implies (from the perspective of critical realism) first describing and conceptualizing the properties and causal mechanisms generating and enabling events, making things happen, and then describing how different mechanisms manifest themselves under specific conditions”
  • Science should have generalizing claims, have methods for validating generalizations

Method

  • Abduction and retroduction central for social science. Pick appropriate method for the object
    • Qualitative case study helps acquire knowledge about laws
  • Empiricist (inductive extrapolation) vs realist (retroductive inference) generalization
    • Realist uses “transfactual argumentation”, moving from empirical to structural. Abstract?
  • Substantiate argument with assertions, observations etc

Inference

  • Ways of reasoning/arguing when relating particular to general
    • Ways of moving “from one thing to something else”
    • Answers questions such as “What does this mean? What follows from this? What must exist for this to be possible?”
    • Logical inferences (deductive) vs ways of reasoning/thought operations (e.g retroductive)
  • Scientific inference partly follows formalized, strict rules of logical argumentation
  • Modes of inference: formal logic (deduction, induction), abduction and retroduction. Complementary in practice. Deductive/inductive logic vs research approach

Analytical inference - no new knowledge about reality

  • Deduction: the only one valid as strictly logical. Indicates what is necessary for a logically valid argument. E.g axiomatic maths
    • Start with established theories, derive hypotheses, then test on “empirical material”
    • Assuming premises are correct, test validity of process used to reach the conclusion from them. Analytical conclusions
    • Propositional (modus ponens/tollens; Hypothetical deductive method) vs predicate logic (“all”, “no”)

Synthetic inference - new knowledge about reality

  • Induction: relatively unprejudiced observations not bound to a theory; still contains interpretation
    • e.g. “grounded theory” approach
    • Generalizations involve uncertainty = “internal limitations”, some conclusions can never be reached = “external limitations”.
      • Can calculate degree of uncertainty statistically w/ assumptions
      • Works better in a “stable reality”; social reality at level of events often unstable, effects depends on context
      • Does not allow to reach knowledge of structure and mechanisms from observables
  • Abduction: “formalized inference” or “inference to the best explanation”. Akinator-style. Involves redescription/recontextualization
    • Start from a rule describing a general pattern; conclusion not logically given in the premise. Conclusion is fallible, a form of hypothesis
      • Relates different knowledge/ideas to each other; Shows how something might be, rather than how it must be (Habermas)
      • New meaning to a known phenomena. Moving from a conception to a potentially deeper/more refined conception
      • Peirce: “From facts of one kind to facts of another”
    • In social science might not be possible to say true or false?
    • Eco: overcoded (automated/natural), undercoded (e.g. choose from several theories), creative abduction
      • Overcoded usually “beyond sphere of criticism”, needs to be reflected upon carefully
    • Relates to production of models that help discover new hypotheses
  • Retroduction: not a formalized mode of inference, unlike others. Tries to uncover internal structure
    • Employs “transcendental argumentation”. Identify necessary conditions. What makes X possible?
    • Habermas: “reconstructive science” for rational comms
    • Example in Baumans’ “What made Holocaust possible”
    • How to arrive at knowledge of deeper structures at play?
      • In natural science traditional experiments and lab conditions provide “closure” that makes retroduction possible
      • In social science: counterfactual thinking, social experiment, studies of “pathological” and “extreme” cases (e.g. crises), comparative case studies

Application: Explanatory model for Critical Realism

Guidelines on relating concrete (stage 1) to abstract (2-5) and back to concrete (6). Synthesis of Bhaskar’s RRRE and DREI models.

  • Stage 1: description
    • Describe event studied, use interpretation and way of describing of people involved. Employ qualitative and quantitative methods (?)
  • Stage 2: analytical resolution
    • Break down complex entities into components/aspects/dimensions. “Scientific analysis”
  • Stage 3: abduction/theoretical redescription
    • Interpret constituent components using “hypothetical conceptual frameworks and theories”. Present, compare and integrate different explanations, theories, interpretations
  • Stage 4: retroduction
    • Use retroductive strategies to identify fundamentally constitutive parts and define what makes the even possible, what causal mechanisms are related
  • Stage 5: comparison between different theories/abstractions
    • Compare, explain, estimate explanatory power of mechanisms and structures from stages 3 and 4
    • See if some theories have greater explanatory power or are complementary to each other
  • Stage 6: concretization and contextualization
    • Understand how mechanisms involved interact with other mechanisms, on which levels, under which conditions
    • Contextualize the work of mechanisms, explain concrete events and processes

References

  1. Karlsson, Berth Danermark, Mats Ekström, Jan Ch. “Generalization, Scientific Inference, and Models for Explanatory Social Science.” In Explaining Society, 2nd ed. Routledge, 2019.